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Author SHA1 Message Date
Amaury JOLY
216083a4cb ajout biblio 2026-04-08 17:06:53 +02:00
Amaury JOLY
d4856e9707 Redaction des deux derniers lemmes du BFT + explication des algos + transition partie crash partie byzantine plus fluide 2026-03-16 09:41:45 +00:00
Amaury JOLY
d629de3670 remove RB for crash algorithms + some syntaxes fix in BFT algo 2026-03-16 09:15:07 +00:00
Amaury JOLY
bee54232af remove redundant lemma and add inclusion lemma 2026-03-05 12:05:17 +00:00
Amaury JOLY
9a9d7af098 redaction des lemmes + preuve 2026-03-05 10:52:29 +00:00
Amaury JOLY
61282a0737 refactoring 2026-03-04 18:38:08 +00:00
Amaury JOLY
e4e3abad91 refacto preuve crash 2026-03-03 12:36:34 +00:00
Amaury JOLY
55fa76a272 refacto algo crash (todo preuve) 2026-03-02 15:10:18 +00:00
Amaury JOLY
d9848967b8 clean de l'algo 2026-03-02 12:59:50 +00:00
Amaury JOLY
cc22c9d7f3 algorithmpseudocode -> algorithm2e 2026-02-22 22:27:01 +01:00
Amaury JOLY
268c30a112 typo et quelques lemmes 2026-02-17 14:30:31 +01:00
Amaury JOLY
921dd502e3 typo 2026-01-26 12:54:25 +01:00
Amaury JOLY
8ae05ff173 huge rearangement + new algo. TODO proof on it 2026-01-23 17:02:27 +01:00
Amaury JOLY
945d830e89 partial-proof on BFT ARB 2026-01-23 11:11:19 +01:00
JOLY Amaury
ea8826c4f5 typos 2026-01-23 07:52:01 +00:00
Amaury JOLY
3e8aec36a2 reformatage 2026-01-20 10:53:00 +01:00
Amaury JOLY
d5a865dd0a fin (?) de la spec de BFT-DL + debut de preuve de l'algo pour BFT ARB 2026-01-20 10:28:46 +01:00
Amaury JOLY
f2cc294232 update de la spéc de BFT-DL + preuve READ Liveness 2026-01-15 12:04:20 +01:00
Amaury JOLY
f5e0d90fb4 update 2026-01-15 09:30:46 +01:00
Amaury JOLY
1acb408d01 presentation ecole d'hiver 2026-01-15 09:30:33 +01:00
Amaury JOLY
106bc70056 update 2026-01-07 20:16:22 +01:00
Amaury JOLY
e89e0e8d2a update 2026-01-07 17:40:57 +01:00
Amaury JOLY
926c3fdc51 update 2026-01-05 17:11:40 +01:00
Amaury JOLY
679e6e949c reorganisation multi-files 2026-01-05 15:31:22 +01:00
20 changed files with 2836 additions and 1005 deletions

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@@ -225,7 +225,7 @@ Each process $p_i$ maintains:
% ------------------------------------------------------------------------------ % ------------------------------------------------------------------------------
\section{Correctness} \section{Correctness}
\begin{lemma}[Stable round closure]\label{lem:closure-stable} \begin{lemma}[Stable round closure]\label{rem:closure-stable}
If a round $r$ is closed, then there exists a linearization point $t_0$ of $\APPEND(r)$ in the \DL, and from that point on, no $\PROVE(r)$ can be valid. If a round $r$ is closed, then there exists a linearization point $t_0$ of $\APPEND(r)$ in the \DL, and from that point on, no $\PROVE(r)$ can be valid.
Once closed, a round never becomes open again. Once closed, a round never becomes open again.
\end{lemma} \end{lemma}

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\subsection{DenyList Object}
We assume a linearizable DenyList (\DL) object, following the specification in~\cite{frey:disc23}, with the following properties.
The DenyList object type supports three operations: $\APPEND$, $\PROVE$, and $\READ$. These operations appear as if executed in a sequence $\Seq$ such that:
\begin{itemize}
\item \textbf{Termination.} A $\PROVE$, an $\APPEND$, or a $\READ$ operation invoked by a correct process always returns.
\item \textbf{APPEND Validity.} The invocation of $\APPEND(x)$ by a process $p$ is valid if:
\begin{itemize}
\item $p \in \Pi_M \subseteq \Pi$; \textbf{and}
\item $x \in S$, where $S$ denote the universe of valid entries to be appended to the DenyList.
\end{itemize}
Otherwise, the operation is invalid.
\item \textbf{PROVE Validity.} Let $op$ the invocation of $\PROVE(x)$ by a process $p_i$. We said $op$ to be invalid, if and only if:
\begin{itemize}
\item $p \not\in \Pi_V \subseteq \Pi$; \textbf{or}
\item A valid $\APPEND(x)$ appears before $op$ in $\Seq$.
\end{itemize}
Otherwise, the operation is said to be valid.
\item \textbf{PROVE Anti-Flickering.} If the invocation of a operation $op = \PROVE(x)$ by a correct process $p \in \Pi_V$ is invalid, then any $\PROVE(x)$ operation that appears after $op$ in $\Seq$ is invalid.
\item \textbf{READ Validity.} The invocation of $op = \READ()$ by a process $p \in \pi_V$ returns the list of valid invocations of $\PROVE$ that appears before $op$ in $\Seq$ along with the names of the processes that invoked each operation.
% \item \textbf{Anonymity.} Let us assume the process $p$ invokes a $\PROVE(v)$ operation. If the process $p'$ invokes a $\READ()$ operation, then $p'$ cannot learn the value $v$ unless $p$ leaks additional information.
\end{itemize}
We assume that $\Pi_M = \Pi_V = \Pi$ (all processes can invoke $\APPEND$ and $\PROVE$).

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Processes export \ABbroadcast$(m)$ and $m = \ABdeliver()$. We adopt the standard Atomic Broadcast specification of~\cite{Defago2004}. \ARB requires the following properties:
\begin{itemize}[leftmargin=*]
\item \textbf{Total Order}:
\begin{equation*}
\forall m_1,m_2,\ \forall p_i,p_j:\ \ (m_1 = \ABdeliver_i()) \prec (m_2 = \ABdeliver_i()) \Rightarrow (m_1 = \ABdeliver_j()) \prec (m_2 = \ABdeliver_j())
\end{equation*}
\item \textbf{Integrity}: Every message delivered was previously broadcast. $\forall p_i:\ m = \ABdeliver_i() \Rightarrow \exists p_j:\ \ABbroadcast_j(m)$.
\item \textbf{No-duplicates}: No message is delivered more than once at any process.
\item \textbf{Validity}: If a correct process broadcasts $m$, every correct process eventually delivers $m$.
\end{itemize}

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We present below an example of implementation of Atomic Reliable Broadcast (\ARB) using point-to-point reliable, error-free channels and a DenyList (\DL) object according to the model and notations defined in Section 2.
\subsection{Algorithm}
\begin{definition}[Closed round]\label{def:closed-round}
Given a \DL{} linearization $H$, a round $r\in\mathcal{R}$ is \emph{closed} in $H$ if $H$ contains an operation $\APPEND(r)$.
Equivalently, there exists a time after which every $\PROVE(r)$ is invalid in $H$.
\end{definition}
% \paragraph{DenyList.} The \DL is initialized empty. We assume $\Pi_M = \Pi_V = \Pi$ (all processes can invoke \APPEND and \PROVE).
\subsubsection{Handlers and Procedures}
\begin{algorithm}[H]
\caption{ARB at process $p_i$}\label{alg:arb-crash}
% \SetAlgoLined
\SetKwBlock{LocalVars}{Local Variables:}{}
\LocalVars{
$\unordered \gets \emptyset$,
$\ordered \gets \epsilon$,
$\delivered \gets \epsilon$\;
$\prop[r][j] \gets \bot,\ \forall r,j$\;
}
\vspace{0.3em}
\For{$r = 1, 2, \ldots$}{
\textbf{wait until} $\unordered \setminus \ordered \neq \emptyset$\;
$S \leftarrow (\unordered \setminus \ordered)$\;\nllabel{code:Sconstruction}
\lForEach{$j \in \Pi$}{
$\send(\texttt{PROP}, S, \langle r, i \rangle) \textbf{ to } p_j$
}
$\PROVE(r)$; $\APPEND(r)$\;\nllabel{code:submit-proposition}
$\winners[r] \gets \{ j : (j, r) \in \READ() \}$\;\nllabel{code:Wcompute}
\textbf{wait until} $\forall j \in \winners[r],\ \prop[r][j] \neq \bot$\;\nllabel{code:check-winners-ack}
$M \gets \bigcup_{j \in \winners[r]} \prop[r][j]$\;\nllabel{code:Mcompute-dl}
$\ordered \leftarrow \ordered \cdot \order(M)$\;\nllabel{code:next-msg-extraction}
}
\vspace{0.3em}
\Upon{$\ABbroadcast(m)$}{
$\unordered \gets \unordered \cup \{m\}$\;\nllabel{code:abbroadcast-add}
}
\vspace{0.3em}
\Upon{$\receive(\texttt{PROP}, S, \langle r, j \rangle)$ from process $p_j$}{
$\unordered \leftarrow \unordered \cup \{S\}$\;\nllabel{code:receivedConstruction}
$\prop[r][j] \leftarrow S$\;\nllabel{code:prop-set}
}
\vspace{0.3em}
\Upon{$\ABdeliver()$}{
\lIf{$\ordered \setminus \delivered = \emptyset$}{
\Return{$\bot$}
}
let $m$ be the first element in $(\ordered \setminus \delivered$)\;\nllabel{code:adeliver-extract}
$\delivered \gets \delivered \cdot m$\;\nllabel{code:adeliver-mark}
\Return{$m$}
}
\end{algorithm}
\paragraph{Algorithm intuition.}
The crash-tolerant algorithm is organized around round closure and winner extraction. By \Cref{def:closed-round,def:first-append,lem:closure-view,lem:winners}, once a round is closed, every correct process eventually reads the same winner set $\Winners_r$. By \Cref{lem:nonempty}, this set is never empty, and by \Cref{lem:winners-propose} every winner has necessarily sent its proposal to all processes before becoming a winner, exactly because sending precedes $\PROVE(r)$ and $\APPEND(r)$ at line~\ref{code:submit-proposition}. Under reliable channels, these winner proposals are eventually received by every correct process, so the waiting condition at line~\ref{code:check-winners-ack} eventually becomes true, which is formalized by \Cref{lem:eventual-closure}. Then, by \Cref{lem:convergence}, all correct processes compute the same set $M$ at line~\ref{code:Mcompute-dl}, and because line~\ref{code:next-msg-extraction} applies the same deterministic ordering function, they append messages in the same order; this is exactly the core mechanism later used in \Cref{lem:validity,lem:no-duplication,lem:total-order}.
\subsection{Correctness}
\begin{definition}[First APPEND]\label{def:first-append}
Given a \DL{} linearization $H$, for any closed round $r\in\mathcal{R}$, we denote by $\APPEND^{(\star)}(r)$ the earliest $\APPEND(r)$ in $H$.
\end{definition}
\begin{remark}[Stable round closure]\label{rem:closure-stable}
If a round $r$ is closed, then there exists a linearization point $t_0$ of $\APPEND(r)$ in the \DL, and from that point on, no $\PROVE(r)$ can be valid.
Once closed, a round never becomes open again.
\end{remark}
\begin{proof}
By \Cref{def:closed-round}, some $\APPEND(r)$ occurs in the linearization $H$. \\
$H$ is a total order of operations, the set of $\APPEND(r)$ operations is totally ordered, and hence there exists a smallest $\APPEND(r)$ in $H$. We denote this operation $\APPEND^{(\star)}(r)$ and $t_0$ its linearization point. \\
By the validity property of \DL, a $\PROVE(r)$ is valid iff $\PROVE(r) \prec \APPEND^{(\star)}(r)$. Thus, after $t_0$, no $\PROVE(r)$ can be valid. \\
$H$ is a immutable grow-only history, and hence once closed, a round never becomes open again. \\
Hence there exists a linearization point $t_0$ of $\APPEND(r)$ in the \DL, and from that point on, no $\PROVE(r)$ can be valid and the closure is stable.
\end{proof}
\begin{lemma}[Across rounds]\label{lem:across}
If there exists a $r$ such that $r$ is closed, $\forall r'$ such that $r' < r$, r' is also closed.
\end{lemma}
\begin{proof}
\emph{Base.} For a closed round $r=0$, the set $\{r' \in \mathcal{R} : r' < r\}$ is empty, so the claim holds.
\emph{Induction step.} Assume $r+1$ is closed. By \cref{def:first-append}, there exists an earliest operation $\APPEND^{(\star)}(r+1)$ in the \DL linearization $H$. Let $p_j$ be the process that invokes this operation.
In Algorithm~\ref{alg:arb-crash}, the call to $\APPEND(\cdot)$ appears at line~\ref{code:submit-proposition}, inside the loop indexed by rounds $1,2,\ldots$. Therefore, if $p_j$ reaches line~\ref{code:submit-proposition} for round $r+1$, then in the previous loop iteration (round $r$) process order implies that $p_j$ has already invoked $\APPEND(r)$ at the same line.
Hence an $\APPEND(r)$ exists in $H$, so round $r$ is closed by \cref{def:closed-round}. We proved:
\[
(r+1\ \text{closed}) \Rightarrow (r\ \text{closed}).
\]
By repeated application, if some round $r$ is closed, then every round $r' < r$ is also closed.
\end{proof}
\begin{definition}[Winner Invariant]\label{def:winner-invariant}
For any closed round $r$, define
\[
\Winners_r \triangleq \{ j : \PROVE_j(r) \prec \APPEND^\star(r) \}
\]
called the unique set of winners of round $r$.
\end{definition}
\begin{lemma}[Invariant view of closure]\label{lem:closure-view}
For any closed round $r$, all correct processes eventually observe the same set of valid tuples $(\ \cdot,r)$ in their \DL view.
\end{lemma}
\begin{proof}
Let's take a closed round $r$. By \Cref{def:first-append}, there exists $\APPEND^{(\star)}(r)$ the earliest $\APPEND(r)$ in the DL linearization.
Consider any correct process $p_i$ that invokes $\READ()$ after $\APPEND^\star(r)$ in the DL linearization. Since $\APPEND^\star(r)$ invalidates all subsequent $\PROVE(r)$, the set of valid tuples $(\_,r)$ retrieved by a $\READ()$ after $\APPEND^\star(r)$ is fixed and identical across all correct processes.
Therefore, for any closed round $r$, all correct processes eventually observe the same set of valid tuples $(\ \cdot,r )$ in their \DL view.
\end{proof}
\begin{lemma}[Well-defined winners]\label{lem:winners}
For any correct process $p_i$ and round $r$, if $p_i$ computes $\winners[r]$ at line~\ref{code:Wcompute}, then :
\begin{itemize}
\item $\Winners_r$ is defined;
\item the computed $\winners[r]$ is exactly $\Winners_r$.
\end{itemize}
\end{lemma}
\begin{proof}
Lets consider a correct process $p_i$ that reach line~\ref{code:Wcompute} to compute $\winners[r]$. \\
By program order, $p_i$ must have executed $\APPEND_i(r)$ at line~\ref{code:submit-proposition} before, which implies by \Cref{def:closed-round} that round $r$ is closed at that point. So by \Cref{def:winner-invariant}, $\Winners_r$ is defined. \\
By \Cref{lem:closure-view}, all correct processes eventually observe the same set of valid tuples $(\ \cdot,r)$ in their \DL view. Hence, when $p_i$ executes the $\READ()$ at line~\ref{code:Wcompute} after the $\APPEND_i(r)$, it observes a set $P$ that includes all valid tuples $(\ \cdot ,r)$ such that
\[
\winners[r] = \{ j : (j,r) \in P \} = \{j : \PROVE_j(r) \prec \APPEND^{(\star)}(r) \} = \Winners_r
\]
\end{proof}
\begin{lemma}[Winners are non-empty]\label{lem:nonempty}
For any closed round $r$, there exists at least one process $p_j$ that invoked $\PROVE_j(r) \prec \APPEND^\star(r)$, so $\Winners_r \neq \emptyset$.
\end{lemma}
\begin{proof}[Proof]
Let $r$ be a closed round. By \Cref{def:closed-round}, some $\APPEND(r)$ occurs in the \DL linearization $H$. Let $p_i$ be the process invoking the earliest such operation, $\APPEND^{(\star)}(r)$.
By program order in Algorithm~\ref{alg:arb-crash}, the call to $\APPEND(\cdot)$ at line~\ref{code:submit-proposition} is immediately preceded by $\PROVE(r)$. Thus $p_i$ must have invoked $\PROVE_i(r)$ before $\APPEND^{(\star)}(r)$, and by the sequence of code at line~\ref{code:submit-proposition}, this $\PROVE_i(r)$ executes before $\APPEND^{(\star)}(r)$ in the linearization.
By \Cref{def:winner-invariant}, $p_i \in \Winners_r$. Hence $\Winners_r \neq \emptyset$.
\end{proof}
\begin{lemma}[Winners must propose]\label{lem:winners-propose}
For any closed round $r$, $\forall i \in \Winners_r$, process $p_i$ must have sent messages to all processes $j \in \Pi$, and hence any correct process $p_j$ will eventually receive $p_i$'s message for round $r$ and set $\prop[r][i]$ to a non-$\bot$ value.
\end{lemma}
\begin{proof}[Proof]
Fix a closed round $r$. By \Cref{def:winner-invariant}, for any $i \in \Winners_r$, there exists a valid $\PROVE_i(r)$ such that $\PROVE_i(r) \prec \APPEND^\star(r)$ in the DL linearization. By program order in Algorithm~\ref{alg:arb-crash}, $p_i$ must have sent messages to all $j \in \Pi$ at line~\ref{code:submit-proposition} before invoking $\PROVE(r)$.
If $p_i$ is a correct process that completed sending to all processes, then by the reliable and error-free nature of the communication channels, every correct process $p_j$ will eventually receive $p_i$'s message, which sets $\prop[r][i] \leftarrow S$ at line~\ref{code:prop-set}. If $p_i$ crashes before sending to all processes, then $p_i$ cannot invoke a valid $\PROVE_i(r)$ afterwards, contradicting the assumption that $i \in \Winners_r$. Hence $p_i$ must have completed sending to all processes.
\end{proof}
\begin{definition}[Messages invariant]\label{def:messages-invariant}
For any closed round $r$ and any correct process $p_i$ such that $\forall j \in \Winners_r : prop^{(i)}[r][j] \neq \bot$, define
\[
\Messages_r \triangleq \bigcup_{j\in\Winners_r} \prop^{(i)}[r][j]
\]
as the set of messages proposed by the winners of round $r$.
\end{definition}
\begin{lemma}[Eventual proposal closure]\label{lem:eventual-closure}
If a correct process $p_i$ define $M$ at line~\ref{code:Mcompute-dl}, then for every $j \in \Winners_r$, $\prop^{(i)}[r][j] \neq \bot$.
\end{lemma}
\begin{proof}[Proof]
Let take a correct process $p_i$ that computes $M$ at line~\ref{code:Mcompute-dl}. By \Cref{lem:winners}, $p_i$ computation is the winner set $\Winners_r$.
By \Cref{lem:nonempty}, $\Winners_r \neq \emptyset$. The instruction at line~\ref{code:Mcompute-dl} where $p_i$ computes $M$ is guarded by the condition at line~\ref{code:check-winners-ack}, which ensures that $p_i$ has received messages from every winner $j \in \Winners_r$. By \Cref{lem:winners-propose}, each winner $j$ has sent messages to all processes including $p_i$. Thus, by the reliable and error-free nature of the channels, if $p_i$ is correct, it will eventually receive $j$'s message, setting $\prop^{(i)}[r][j] \neq \bot$ at line~\ref{code:prop-set}. Hence, $\prop^{(i)}[r][j] \neq \bot$ for all $j \in \Winners_r$.
\end{proof}
\begin{lemma}[Unique proposal per sender per round]\label{lem:unique-proposal}
For any round $r$ and any process $p_i$, $p_i$ sends messages to all processes at most once for each round.
\end{lemma}
\begin{proof}[Proof]
In Algorithm~\ref{alg:arb-crash}, the only place where a process $p_i$ can send messages to all processes is at line~\ref{code:submit-proposition}, which appears inside the main loop indexed by rounds $r = 1, 2, \ldots$.
Each iteration of this loop processes exactly one round value $r$, and within that iteration, messages are sent at most once (before the $\PROVE(r)$ and $\APPEND(r)$ calls). Since the loop variable $r$ takes each value $1, 2, \ldots$ at most once during the execution, process $p_i$ sends messages at most once for any given round $r$.
\end{proof}
\begin{lemma}[Proposal convergence]\label{lem:convergence}
For any round $r$, for any correct processes $p_i$ that execute line~\ref{code:Mcompute-dl}, we have
\[
M^{(i)} = \Messages_r
\]
\end{lemma}
\begin{proof}[Proof]
Let take a correct process $p_i$ that compute $M$ at line~\ref{code:Mcompute-dl}. That implies that $p_i$ has defined $\winners r$ at line~\ref{code:Wcompute}. It implies that, by \Cref{lem:winners}, $r$ is closed and $\winners_r = \Winners_r$. \\
By \Cref{lem:eventual-closure}, for every $j \in \Winners_r$, $\prop^{(i)}[r][j] \neq \bot$. By \Cref{lem:unique-proposal}, each winner $j$ sends messages to all processes at most once per round. Thus, $\prop^{(i)}[r][j] = S^{(j)}$ is uniquely defined as the messages sent by $j$ in that round. Hence, when $p_i$ computes
\[
M^{(i)} = \bigcup_{j\in\Winners_r} \prop^{(i)}[r][j] = \bigcup_{j\in\Winners_r} S^{(j)} = \Messages_r.
\]
\end{proof}
\begin{lemma}[Inclusion]\label{lem:inclusion}
If some correct process invokes $\ABbroadcast(m)$, then there exist a round $r$ and a process $j\in\Winners_r$ such that $p_j$ sends a proposal $S$ to all processes at line~\ref{code:submit-proposition} with $m\in S$.
\end{lemma}
\begin{proof}
Let $p_i$ be a correct process that invokes $\ABbroadcast(m)$. By the handler at line~\ref{code:abbroadcast-add}, $m$ is added to $\unordered$. Since $p_i$ is correct, it continues executing the main loop.
Consider any iteration of the loop where $p_i$ executes line~\ref{code:Sconstruction} while $m \in (\unordered \setminus \ordered)$. At that iteration, for some round $r$, process $p_i$ constructs $S$ containing $m$ and sends $S$ to all processes at line~\ref{code:submit-proposition}.
We distinguish two cases:
\begin{itemize}
\item \textbf{Case 1: $p_i$ is a winner.} If $p_i \in \Winners_r$ for this round $r$, then by \Cref{def:winner-invariant} and program order, $p_i$ has sent proposal $S$ to all processes with $m \in S$, and the lemma holds with $j = i$.
\item \textbf{Case 2: $p_i$ is not a winner.} If $p_i \notin \Winners_r$, then $p_i$ is still a correct process, so it has sent its proposal $S$ (containing $m$) to all processes in $\Pi$. By the reliable and error-free nature of the communication channels, all correct processes will eventually receive $p_i$'s message. By line~\ref{code:receivedConstruction}, each correct process $p_k$ adds $m$ to its own $\unordered$ set. Hence every correct process will eventually attempt to broadcast $m$ in some subsequent round.
Since there are infinitely many rounds and finitely many processes, and by \Cref{lem:nonempty} every closed round has at least one winner, there must exist a round $r'$ and a correct process $p_j \in \Winners_{r'}$ such that $m \in (\unordered \setminus \ordered)$ when $p_j$ constructs its proposal $S$ at line~\ref{code:Sconstruction} for round $r'$. Hence $p_j$ sends messages $S$ with $m \in S$ at line~\ref{code:submit-proposition}.
\end{itemize}
In both cases, there exists a round and a winner whose proposal includes $m$.
\end{proof}
\begin{lemma}[Broadcast Termination]\label{lem:bcast-termination}
A correct process which invokes $\ABbroadcast(m)$ eventually exits the function and returns.
\end{lemma}
\begin{proof}[Proof]
By Algorithm~\ref{alg:arb-crash}, the handler for $\ABbroadcast(m)$ at line~\ref{code:abbroadcast-add} performs a single local operation: adding $m$ to the local set $\unordered$. This operation terminates immediately and the function returns.
\end{proof}
\begin{lemma}[Validity]\label{lem:validity}
If a correct process $p$ invokes $\ABbroadcast(m)$, then every correct process that invokes a infinitely many times $\ABdeliver()$ eventually delivers $m$.
\end{lemma}
\begin{proof}[Proof]
Let $p_i$ a correct process that invokes $\ABbroadcast(m)$ and $p_q$ a correct process that infinitely invokes $\ABdeliver()$. By \Cref{lem:inclusion}, there exist a closed round $r$ and a correct process $j\in\Winners_r$ such that $p_j$ sends a proposal $S$ to all processes with $m\in S$.
By \Cref{lem:eventual-closure}, when $p_q$ computes $M$ at line~\ref{code:Mcompute-dl}, $\prop[r][j]$ is non-$\bot$ because $j \in \Winners_r$. By \Cref{lem:unique-proposal}, $p_j$ sends messages at most once per round, so $\prop[r][j]$ is uniquely defined as the proposal sent by $j$. Hence, when $p_q$ computes
\[
M = \bigcup_{k\in\Winners_r} \prop[r][k],
\]
we have $m \in \prop[r][j] = S$, so $m \in M$. By \Cref{lem:convergence}, $M$ is invariant so each computation of $M$ by a correct process includes $m$. At each invocation of $m' = \ABdeliver()$, $m'$ is added to $\delivered$ until $M \subseteq \delivered$. Once this happens we're assured that there exists an invocation of $\ABdeliver()$ which return $m$. Hence $m$ is well delivered.
\end{proof}
\begin{lemma}[No duplication]\label{lem:no-duplication}
No correct process delivers the same message more than once.
\end{lemma}
\begin{proof}
Let consider two invokations of $\ABdeliver()$ made by the same correct process which returns $m$. Let call these two invocations respectively $\ABdeliver^{(A)}()$ and $\ABdeliver^{(B)}()$.
When $\ABdeliver^{(A)}()$ occurs, by program order and because it reached line~\ref{code:adeliver-mark} to return $m$, the process must have add $m$ to $\delivered$. Hence when $\ABdeliver^{(B)}()$ reached line~\ref{code:adeliver-extract} to extract the next message to deliver, it can't be $m$ because $m \not\in (\ordered \setminus \delivered)$. So a $\ABdeliver^{(B)}()$ which delivers $m$ can't occur.
\end{proof}
\begin{lemma}[Total order]\label{lem:total-order}
For any two messages $m_1$ and $m_2$ delivered by correct processes, if a correct process $p_i$ delivers $m_1$ before $m_2$, then any correct process $p_j$ that delivers both $m_1$ and $m_2$ delivers $m_1$ before $m_2$.
\end{lemma}
\begin{proof}
Consider a correct process that delivers both $m_1$ and $m_2$. By \Cref{lem:validity}, there exists closed rounds $r_1$ and $r_2$ and correct processes $k_1 \in \Winners_{r_1}$ and $k_2 \in \Winners_{r_2}$ such that $p_{k_1}$ and $p_{k_2}$ send proposals $S_1$ and $S_2$ respectively, with $m_1\in S_1$ and $m_2\in S_2$.
Let consider two cases :
\begin{itemize}
\item \textbf{Case 1:} $r_1 < r_2$. By program order, any correct process must have waited to append in $\delivered$ every messages in $M$ (which contains $m_1$) to increment $\current$ and eventually set $\current = r_2$ to compute $M$ and then invoke the $ m_2 = \ABdeliver()$. Hence, for any correct process that delivers both $m_1$ and $m_2$, it delivers $m_1$ before $m_2$.
\item \textbf{Case 2:} $r_1 = r_2$. By \Cref{lem:convergence}, any correct process that computes $M$ at line~\ref{code:Mcompute-dl} computes the same set of messages $\Messages_{r_1}$. By line~\ref{code:next-msg-extraction} the messages are pull in a deterministic order defined by $\ordered(\_)$. Hence, for any correct process that delivers both $m_1$ and $m_2$, it delivers $m_1$ and $m_2$ in the deterministic order defined by $\ordered(\_)$.
\end{itemize}
In all possible cases, any correct process that delivers both $m_1$ and $m_2$ delivers $m_1$ and $m_2$ in the same order.
\end{proof}
\begin{theorem}[\ARB]
In a crash asynchronous message-passing system with reliable, error-free communication channels, assuming a synchronous DenyList ($\DL$) object, the algorithm implements Atomic Reliable Broadcast.
\end{theorem}
\begin{proof}
We show that the algorithm satisfies the properties of Atomic Reliable Broadcast under the assumed $\DL$ synchrony and reliable channel assumption.
First, by \Cref{lem:bcast-termination}, if a correct process invokes $\ABbroadcast(m)$, then it eventually returns from this invocation.
Moreover, \Cref{lem:validity} states that if a correct process invokes $\ABbroadcast(m)$, then every correct process that invokes $\ABdeliver()$ infinitely often eventually delivers $m$.
This gives the usual Validity property of $\ARB$.
Concerning Integrity and No-duplicates, the construction only ever delivers messages that have been obtained from processes that constructed and sent them in the algorithm.
Every delivered message was previously sent by some process at line~\ref{code:submit-proposition}, so no spurious messages are delivered.
In addition, \Cref{lem:no-duplication} states that no correct process delivers the same message more than once.
Together, these arguments yield the Integrity and No-duplicates properties required by $\ARB$.
For the ordering guarantees, \Cref{lem:total-order} shows that for any two messages $m_1$ and $m_2$ delivered by correct processes, every correct process that delivers both $m_1$ and $m_2$ delivers them in the same order.
Hence all correct processes share a common total order on delivered messages.
All the above lemmas are proved under the assumptions that $\DL$ satisfies the required synchrony properties and that the communication channels are reliable and error-free (no message loss or corruption).
Therefore, under these assumptions, the algorithm satisfies Validity, Integrity/No-duplicates, and total order, and hence implements Atomic Reliable Broadcast, as claimed.
\end{proof}
\subsection{Reciprocity}
% ------------------------------------------------------------------------------
So far, we assumed the existence of a synchronous DenyList ($\DL$) object and showed how to build an Atomic Reliable Broadcast ($\ARB$) primitive using reliable, error-free point-to-point channels. We now briefly argue that, conversely, an $\ARB$ primitive is strong enough to implement a synchronous $\DL$ object.
\xspace
\paragraph{DenyList as a deterministic state machine.}
Without anonymity, the \DL specification defines a
deterministic abstract object: given a sequence $\Seq$ of operations
$\APPEND(x)$, $\PROVE(x)$, and $\READ()$, the resulting sequence of return
values and the evolution of the abstract state (set of appended elements,
history of operations) are uniquely determined.
\paragraph{State machine replication over \ARB.}
Assume a system that exports a FIFO-\ARB primitive with the guarantees that if a correct process invokes $\ABbroadcast(m)$, then every correct process eventually $\ABdeliver(m)$ and the invocation eventually returns.
Following the classical \emph{state machine replication} approach described by Schneider~\cite{Schneider90}, we can implement a fault-tolerant service by ensuring the following properties:
\begin{quote}
\textbf{Agreement.} Every nonfaulty state machine replica receives every request. \\
\textbf{Order.} Every nonfaulty state machine replica processes the requests it receives in
the same relative order.
\end{quote}
Which are cover by our FIFO-\ARB specification.
\paragraph{Correctness.}
\begin{theorem}[From \ARB to synchronous \DL]\label{thm:arb-to-dl}
In an asynchronous message-passing system with crash failures, assume a FIFO Atomic Reliable Broadcast primitive (in the standard Total Order / Atomic Broadcast sense of~\cite{Defago2004}) with Integrity, No-duplicates, Validity, and the liveness of $\ABbroadcast$. Then there exists an implementation of a DenyList object that satisfies Termination, Validity, and Anti-flickering properties.
\end{theorem}
\begin{proof}
Because the \DL object is deterministic, all correct processes see the same sequence of operations and compute the same sequence of states and return values. We obtain:
\begin{itemize}[leftmargin=*]
\item \textbf{Termination.} The liveness of \ARB ensures that each $\ABbroadcast$ invocation by a correct process eventually returns, and the corresponding operation is eventually delivered and applied at all correct processes. Thus every $\APPEND$, $\PROVE$, and $\READ$ operation invoked by a correct process eventually returns.
\item \textbf{APPEND/PROVE/READ Validity.} The local code that forms \ABbroadcast requests can achieve the same preconditions as in the abstract \DL specification (e.g., $p\in\Pi_M$, $x\in S$ for $\APPEND(x)$). Once an operation is delivered, its effect and return value are exactly those of the sequential \DL specification applied in the common order.
\item \textbf{PROVE Anti-Flickering.} In the sequential \DL specification, once an element $x$ has been appended, all subsequent $\PROVE(x)$ are invalid forever. Since all replicas apply operations in the same order, this property holds in every execution of the replicated implementation: after the first linearization point of $\APPEND(x)$, no later $\PROVE(x)$ can return valid at any correct process.
\end{itemize}
Formally, we can describe the \DL object with the state machine approach for
crash-fault, asynchronous message-passing systems with a total order broadcast
layer~\cite{Schneider90}.
\end{proof}
\subsubsection{Example executions}
% \begin{figure}
% \centering
% \resizebox{0.4\textwidth}{!}{
% \input{diagrams/nonBFT_behaviour.tex}
% }
% \caption{Example execution of the ARB algorithm in a non-BFT setting}
% \end{figure}
% \begin{figure}
% \centering
% \resizebox{0.4\textwidth}{!}{
% \input{diagrams/BFT_behaviour.tex}
% }
% \caption{Example execution of the ARB algorithm with a byzantine process}
% \end{figure}
% font en fonctin de lusage
% winner invariant
% order invariant

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\subsection{Model extension}
We extend the crash model of Section 1 (same process universe, asynchronous setting, uniquely identifiable messages, and reliable point-to-point channels) with Byzantine faults and Byzantine-resilient dissemination primitives.
\paragraph{Failure threshold.} At most $t$ processes may be Byzantine, and we assume $n > 3t$, following standard asynchronous Byzantine assumptions~\cite{Bracha87}.
\paragraph{Additional communication primitive.} In addition to reliable point-to-point channels, processes use Reliable Broadcast ($\RB$) with operations $\RBcast(m)$ and $m=\rdeliver()$. We use Bracha's Byzantine RB specification~\cite{Bracha87}: for a fixed sender and broadcast instance, all correct processes that deliver, deliver the same payload, and Byzantine equivocation on that instance is prevented.
\paragraph{Byzantine behaviour}
A Byzantine process may deviate arbitrarily from the algorithm (malformed inputs, selective omission, collusion, inconsistent timing, etc.).
Byzantine processes are still constrained by the assumed primitives: they cannot violate the safety/liveness guarantees of $\DL$ and cannot break the Integrity, No-duplicates, and Validity guarantees of $\RB$.
\paragraph{Notation.} For any indice $k$ we defined by $\DL[k]$ as the $k$-th DenyList object. For a given $\DL[k]$ and any indice $x$ we defined by $\Pi_x^k$ a subset of $\Pi$. Still for a given $k$ we consider $\Pi_M^k \subseteq \Pi$ and $\Pi_V^k \subseteq \Pi$ two authorization subsets for $\DL[k]$. Indice $i \in \Pi$ refer to processes, and $p_i$ denotes the process with identifier $i$. Let $\mathcal{M}$ denote the universe of uniquely identifiable messages, with $m \in \mathcal{M}$. Let $\mathcal{R} \subseteq \mathbb{N}$ be the set of round identifiers; we write $r \in \mathcal{R}$ for a round. We use the precedence relation $\prec_k$ for the $\DL[k]$ linearization: $x \prec_k y$ means that operation $x$ appears strictly before $y$ in the linearized history of $\DL[k]$. For any finite set $A \subseteq \mathcal{M}$, \ordered$(A)$ returns a deterministic total order over $A$ (e.g., lexicographic order on $(\textit{senderId},\textit{messageId})$ or on message hashes).
For any operation $F \in O$,$F_i(...)$ denotes that the operation $F$ is invoked by process $p_i$, and by $F_i^k(...)$ the same operation invoked on the $\DL[k]$ object.
% ------------------------------------------------------------------------------
\subsection{Primitives}
\subsection{Reliable Broadcast (RB)}
\RB provides the following properties in this model (cf.~\cite{Bracha87}).
\begin{itemize}[leftmargin=*]
\item \textbf{Integrity}: Every message received was previously sent. $\forall p_i:\ m = \rbreceived_i() \Rightarrow \exists p_j:\ \RBcast_j(m)$.
\item \textbf{No-duplicates}: No message is received more than once at any process.
\item \textbf{Validity}: If a correct process broadcasts $m$, every correct process eventually receives $m$.
\end{itemize}
\subsubsection{t-BFT-DL}
We consider a t-Byzantine Fault Tolerant DenyList (t-$\BFTDL$) with the following properties.
There are 3 operations : $\BFTPROVE(x), \BFTAPPEND(x), \BFTREAD()$ such that :
\paragraph{Termination.} Every operation $\BFTAPPEND(x)$, $\BFTPROVE(x)$, and $\BFTREAD()$ invoked by a correct process always returns.
\paragraph{PROVE Validity.} The invocation of $op = \BFTPROVE(x)$ by a correct process is valid iff there exist a set of correct process $C$ such that $\forall c \in C$, $c$ invoke $op_2 = \BFTAPPEND(x)$ with $op_2 \prec op_1$ and $|C| \leq t$
\paragraph{PROVE Anti-Flickering.} If the invocation of a operation $op = \BFTPROVE(x)$ by a correct process $p \in \Pi_V$ is invalid, then any $\BFTPROVE(x)$ operation that appears after $op$ in $\Seq$ is invalid.
\paragraph{READ Liveness.} Let $op = \BFTREAD()$ invoke by a correct process such that $R$ is the result of $op$. For all $(i, x) \in R$ there exist a valid invocation of $\BFTPROVE(x)$ by $p_i$.
\paragraph{READ Anti-Flickering.} Let $op_1, op_2$ two $\BFTREAD()$ operations that returns respectively $R_1, R_2$. Iff $op_1 \prec op_2$ then $R_2 \subseteq R_1$. Otherwise $R_1 \subseteq R_2$.
\paragraph{READ Safety.} Let $op_1, op_2$ respectively a valid $\BFTPROVE(x)$ operation submited by the process $p_i$ and a $\BFTREAD()$ operation submited by any correct process such that $op_1 \prec op_2$. Let $R$ the result of $op_2$ then $R \ni (i, x)$
\subsection{DL $\Rightarrow$ t-BFT-DL}
Fix $3t < |M|$. Let
\[
\mathcal{U} = \{\, U \subseteq M \mid |U| = |M| - t \,\}.
\]
For each $U \in \mathcal{U}$, we instantiate one DenyList object $DL_U$ whose authorization sets are
\[
\Pi_M(DL_T) = S_T = U
\qquad\text{and}\qquad
\Pi_V(DL_T) = V.
\]
\[
|\mathcal{U}| = \binom{|M|}{|M| - t}.
\]
\begin{algorithm}
\caption{t-BFT-DL implementation using multiple DL objects}
\Fn{$\BFTAPPEND(x)$}{
\For{\textbf{each } $U \in \mathcal{U}$ st $i \in U$}{
$DL_U.\APPEND(x)$\;
}
}
\vspace{1em}
\Fn{$\BFTPROVE(x)$}{
$\state \gets false$\;
\For{\textbf{each } $U \in \mathcal{U}$}{
$\state \gets \state \textbf{ OR } DL_U.\PROVE(x)$\;\nllabel{code:prove-or}
}
\Return{$\state$}\;
}
\vspace{1em}
\Fn{$\BFTREAD()$}{
$\results \gets \emptyset$\;
\For{\textbf{each } $U \in \mathcal{U}$}{
$\results \gets \results \cup DL_U.\READ()$\;
}
\Return{$\results$}\;
}
\end{algorithm}
\paragraph{Algorithm intuition.}
In the Byzantine setting, a process identifier $j$ is selected in $\winners[r]$ only when it accumulates at least $t+1$ proofs for round $r$ in $\validated(r)$. A process emits such a proof for $j$ only after receiving $j$'s $\texttt{PROP}$ payload (handler $\rdeliver(\texttt{PROP},\cdot)$). Therefore, if $j$ is a winner, at least one correct process has received $j$'s proposal. By RB agreement/validity, once one correct process receives that proposal for the instance, all correct processes eventually receive the same payload, so winner proposals eventually become available everywhere and can be merged consistently.
\begin{lemma}[BFT-PROVE Validity]\label{lem:bft-prove-validity}
The invocation of $op = \BFTPROVE(x)$ by a correct process is invalid iff there exist at least $t+1$ distinct processes in $M$ that invoked a valid $\BFTAPPEND(x)$ before $op$ in $\Seq$.
\end{lemma}
\begin{proof}
Let $op=\BFTPROVE(x)$ be an invocation by a correct process $p_i$. Let $A\subseteq M$ be the set of distinct issuers that invoked $\BFTAPPEND(x)$ before $op$ in $\Seq$.
\begin{itemize}
\item \textbf{Case (i): $|A|\ge t+1$.}
Fix any $U\in\mathcal{U}$. $A\cap U\neq\emptyset$. Pick $j\in A\cap U$. Since $j\in U$, the call $\BFTAPPEND_j(x)$ triggers $DL_U.\APPEND(x)$, and because $\BFTAPPEND_j(x)\prec op$ in $\Seq$, this induces a valid $DL_U.\APPEND(x)$ that appears before the induced $DL_U.\PROVE(x)$ by $p_i$. By \textbf{PROVE Validity} of $\DL$, the induced $DL_U.\PROVE(x)$ is invalid. As this holds for every $U\in\mathcal{U}$, there is \emph{no} component $DL_U$ where $\PROVE(x)$ is valid, so the field $\state$ at line~\ref{code:prove-or} is never becoming true, and $op$ return false.
\item \textbf{Case (ii): $|A|\le t$.}
There exists $U^\star\in\mathcal{U}$ such that $A\cap U^\star=\emptyset$. For any $j\in A$, we have $j\notin U^\star$, so $\BFTAPPEND_j(x)$ does \emph{not} call $DL_{U^\star}.\APPEND(x)$. Hence no valid $DL_{U^\star}.\APPEND(x)$ appears before the induced $DL_{U^\star}.\PROVE(x)$. Since also $i\in \Pi_V(DL_{U^\star})$, by \textbf{PROVE Validity} of $\DL$ the induced $DL_{U^\star}.\PROVE(x)$ is valid. Therefore, there exists a component with a valid $\PROVE(x)$, so $op$ is valid.
\end{itemize}
\smallskip
Combining the cases yields the claimed characterization of invalidity.
\end{proof}
\begin{lemma}[BFT-PROVE Anti-Flickering]\label{lem:bft-prove-anti-flickering}
If the invocation of a operation $op = \BFTPROVE(x)$ by a correct process $p \in \Pi_V$ is invalid, then any $\BFTPROVE(x)$ operation that appears after $op$ in $\Seq$ is invalid.
\end{lemma}
\begin{proof}
Let $op=\BFTPROVE(x)$ be an invocation by a correct process $p_i$ that is \emph{invalid} in $\Seq$.
By BFT-PROVE Validity, this implies that there exist at least $t+1$ \emph{distinct} processes in $M$ that invoked a \emph{valid} $\BFTAPPEND(x)$ before $op$ in $\Seq$. Let $A\subseteq M$ denote that set, with $|A|\ge t+1$.
Fix any $U\in\mathcal{U}$. We have $A\cap U\neq\emptyset$. Pick $j\in A\cap U$. Since $j\in U$, the call $\BFTAPPEND_j(x)$ triggers a call $DL_U.\APPEND(x)$. Moreover, because $\BFTAPPEND_j(x)\prec op$ in $\Seq$, the induced $DL_U.\APPEND(x)$ appears before the induced $DL_U.\PROVE(x)$ of $op$ in the projection $\Seq_U$.
Hence, in $\Seq_U$, there exists a \emph{valid} $DL_U.\APPEND(x)$ that appears before the $DL_U.\PROVE(x)$ induced by $op$. By \textbf{PROVE Validity} the base $\DL$ object, the induced $DL_U.\PROVE(x)$ is therefore \emph{invalid} in $\Seq_U$.
Let $op'=\BFTPROVE(x)$ be any invocation such that $op\prec op'$ in $\Seq$. Fix again any $U\in\mathcal{U}$. Hence, the $DL_U.\PROVE(x)$ induced by $op'$ appears after the $DL_U.\PROVE(x)$ induced by $op$ in $\Seq_U$. Since the induced $DL_U.\PROVE(x)$ of $op$ is invalid, by \textbf{PROVE Anti-Flickering} of $\DL$, \emph{every} subsequent $DL_U.\PROVE(x)$ in $\Seq_U$ is invalid.
As this holds for every $U\in\mathcal{U}$, there is no component $DL_U$ in which the induced $\PROVE(x)$ of $op'$ is valid.
\end{proof}
\begin{lemma}[BFT-READ Liveness]
Let $op = \BFTREAD()$ invoke by a correct process such that $R$ is the result of $op$. For all $(i, x) \in R$ there exist a valid invocation of $\BFTPROVE(x)$ by $p_i$.
\end{lemma}
\begin{proof}
Let $R$ the result of a $READ()$ operation submit by any correct process. $(i, x) \in R$ implie that $\exists U^\star \in \mathcal{U}$ such that $(i, x) \in R^{U^\star}$ with $R^{U^\star}$ the result of $DL_{U^\star}.\READ()$. By \textbf{READ Validity} $(i, x) \in R^{U^\star}$ implie that there exist a valid $DL_{U^\star}.\PROVE_i(x)$. The for loop in the $\BFTPROVE(x)$ implementation return true iff there at least one valid $DL_{U}.\PROVE_i(x)$ for any $U \in \mathcal{U}$.
Hence because there exist a $U^\star$ such that $DL_{U^\star}.\PROVE_i(x)$, there exist a valid $\BFTPROVE_i(x)$.
$(i, x) \in R \implies \exists \BFTPROVE_i(x)$
\end{proof}
\begin{lemma}[BFT-READ Anti-Flickering]\label{lem:bft-read-anti-flickering}
Let $op_1, op_2$ two $\BFTREAD()$ operations that returns respectively $R_1, R_2$. Iff $op_1 \prec op_2$ then $R_2 \subseteq R_1$. Otherwise $R_1 \subseteq R_2$.
\end{lemma}
\begin{proof}
Let $R_1, R_2$ respectively the output of two $\BFTREAD()$ operations $op_1, op_2$ such that $op_1 \prec op_2$.
By the implementation of $\BFTREAD$, $R_k = \bigcup_{U \in \mathcal{U}} R_k^U$ where $R_k^U$ is the result of $DL_U.\READ()$ during $op_k$.
Because $op_1 \prec op_2$ for any $U \in \mathcal{U}$, the $DL_U.\READ()$ induced by $op_1$ happen before the $DL_U.\READ()$ induced by $op_2$. Hence we have for all $U, R_2^U \subseteq R_1^U$.
Therefore
\[
\bigcup_U R_2^U \subseteq \bigcup_U R_1^U \implies
R_2 \subseteq R_1
\]
\end{proof}
\begin{lemma}[BFT-READ Safety]\label{lem:bft-read-safety}
Let $op_1, op_2$ respectively a valid $\BFTPROVE(x)$ operation submited by the process $p_i$ and a $\BFTREAD()$ operation submited by any correct process such that $op_1 \prec op_2$. Let $R$ the result of $op_2$ then $R \ni (i, x)$
\end{lemma}
\begin{proof}
Let $op_1 = \BFTPROVE_i(x)$ be a valid operation by a correct process $p_i$ and $op_2 = \BFTREAD()$ be any $\BFTREAD()$ operation such that $op_1 \prec op_2$ in $\Seq$.
By BFT-PROVE Validity, there exist at most $t$ distinct processes in $M$ that invoked a valid $\BFTAPPEND(x)$ before $op_1$ in $\Seq$. Let $A\subseteq M$ denote that set, with $|A|\le t$.
There exists $U^\star\in\mathcal{U}$ such that $A\cap U^\star=\emptyset$. For any $j\in A$, we have $j\notin U^\star$, so $\BFTAPPEND^{(j)}(x)$ does \emph{not} call $DL_{U^\star}.\APPEND(x)$. Hence no valid $DL_{U^\star}.\APPEND(x)$ appears before the induced $DL_{U^\star}.\PROVE(x)$ of $op_1$. Since also $i\in \Pi_V(DL_{U^\star})$, by \textbf{PROVE Validity} of $\DL$ the induced $DL_{U^\star}.\PROVE_i(x)$ is valid.
Now, because $op_1 \prec op_2$ in $\Seq$, the induced $DL_{U^\star}.\PROVE_i(x)$ appears before the induced $DL_{U^\star}.\READ()$ of $op_2$ in $\Seq_{U^\star}$. By \textbf{READ Safety} of $\DL$, the result $R^{U^\star}$ of the induced $DL_{U^\star}.\READ()$ contains $(i, x)$.
Finally, by the implementation of $\BFTREAD()$, we have $R = \bigcup_{U \in \mathcal{U}} R^U$, so $(i, x) \in R$.
\end{proof}
\begin{theorem}
For any fixed value $t$ such that $3t < |M|$, multiple DenyList Object can be used to implement a t-Byzantine Fault Tolerant DenyList Object.
\end{theorem}
\begin{proof}
Follows directly from the previous lemmas.
\end{proof}
\subsection{Algorithm}
\begin{algorithm}[H]
\caption{t-BFT ARB at process $p_i$}\label{alg:bft-arb}
\SetKwBlock{LocalVars}{Local Variables:}{}
\LocalVars{
$\unordered \gets \emptyset$,
$\ordered \gets \epsilon$,
$\delivered \gets \epsilon$\;
$\prop[r][j] \gets \bot, \forall j, r \in \Pi \times \mathbb{N}$\;
$\done[r] \gets \emptyset, \forall r \in \mathbb{N}$\;
}
\vspace{0.3em}
\For{$r = 1, 2, \ldots$}{\nllabel{alg:main-loop}
\textbf{wait until} $\unordered \setminus \ordered \neq \emptyset$\;
$S \gets \unordered \setminus \ordered$;
$\RBcast(\texttt{PROP}, S, \langle i, r \rangle)$\;
\textbf{wait until} $|\validated(r)| \geq n - t$\;\nllabel{alg:check-validated}
\BlankLine
\lForEach{$j \in \Pi$}{
$\BFTAPPEND(\langle j, r\rangle)$\nllabel{alg:append}
}
\lForEach{$j \in \Pi$}{
$\send(\texttt{DONE}, r)$ \textbf{ to } $p_j$
}
\BlankLine
\textbf{wait until} $|\done[r]| \geq n - t$\;\nllabel{alg:check-done}
\textbf{wait until} $\forall j \in \winners[r],\ \prop[r][j] \neq \bot$ \textbf{ with } $\winners[r] \gets \validated(r)$\;
\BlankLine
$M \gets \bigcup_{j \in \winners[r]} \prop[r][j]$\;\nllabel{code:Mcompute}
$\ordered \gets \ordered \cdot \order(M)$\;
}
\vspace{0.3em}
\Fn{\validated($r$)}{
\Return{$\{j: |\{k: (k, r) \in \BFTREAD()\}| \geq t+1\}$}\;
}
\vspace{0.3em}
\Upon{$\ABbroadcast(m)$}{
$\unordered \gets \unordered \cup \{m\}$\;
}
\vspace{0.3em}
\Upon{$\rdeliver(\texttt{PROP}, S, \langle j, r \rangle)$ from process $p_j$}{
$\unordered \gets \unordered \cup S$;
$\prop[r][j] \gets S$\;
$\BFTPROVE(\langle j, r\rangle)$\;
}
\vspace{0.3em}
\Upon{$\receive(\texttt{DONE}, r)$ from process $p_j$}{
$\done[r] \gets \done[r] \cup \{j\}$\;
}
\vspace{0.3em}
\Upon{$\ABdeliver()$}{
\lIf{$\ordered \setminus \delivered = \emptyset$}{
\Return{$\bot$}
}
let $m$ be the first message in $(\ordered \setminus \delivered)$\;
$\delivered \gets \delivered \cdot \{m\}$\;
\Return{$m$}
}
\end{algorithm}
\paragraph{Algorithm intuition.}
The Byzantine-tolerant construction combines threshold evidence and RB agreement to make winner selection robust. A sender $j$ appears in $\validated(r)$ only when at least $t+1$ proofs for $\langle j,r\rangle$ are observed through $\BFTREAD()$, and by \Cref{lem:bft-prove-validity} this threshold means that $j$ cannot be certified without broad enough support from the system. Once a round is closed, the winner set becomes stable by \Cref{lem:winners-stability}, so correct processes stop diverging on who contributes to the round outcome. For each stable winner, the associated proposal payload is unique at correct receivers by \Cref{lem:bft-unique-proposal}, which prevents equivocation from creating distinct local values for the same winner identity. Consequently, when correct processes wait for all winner proposals and compute the union at line~\ref{code:Mcompute}, they obtain the same message set by \Cref{lem:message-content-invariance}. Progress is then ensured by \Cref{lem:bft-eventual-closure}, which guarantees that if new messages remain unordered, a new round eventually closes with at least $n-t$ winners. Finally, once rounds are commonly closed, appending $\order(M)$ at each round yields a common delivery sequence, exactly formalized by \Cref{lem:bft-total-order}.
% \textbf{Everything below has to be updated}
% \begin{definition}[BFT Closed round for $k$]
% Given $Seq^{k}$ the linearization of the $\BFTDL$ $Y[k]$, a round $r \in \mathcal{R}$ is \emph{closed} in $\Seq$ iff there exist at least $n - f$ distinct processes $j \in \Pi$ such that $\BFTAPPEND_j(r)$ appears in $\Seq^k$. Let call $\BFTAPPEND(r)^\star$ the $(n-f)^{th}$ $\BFTAPPEND(r)$.
% \end{definition}
% \begin{definition}[BFT Closed round]\label{def:bft-closed-round}
% A round $r \in \mathcal{R}$ is \emph{closed} iff for all $\DL[k]$, $r$ is closed in $\Seq^k$.
% \end{definition}
% \subsection{Proof of correctness}
% \begin{remark}[BFT Stable round closure]\label{rem:bft-stable-round-closure}
% If a round $r$ is closed, no more $\BFTPROVE(r)$ can be valid and thus linearized. In other words, once $\BFTAPPEND(r)^\star$ is linearized, no more process can make a proof on round $r$, and the set of valid proofs for round $r$ is fixed. Therefore $\Winners_r$ is fixed.
% \end{remark}
% \begin{proof}
% By definition $r$ closed means that for all process $p_i$, there exist at least $n - f$ distinct processes $j \in \Pi$ such that $\BFTAPPEND_j(r)$ appears in $\Seq^k$. By BFT-PROVE Validity, any subsequent $\BFTPROVE(r)$ is invalid because at least $n - f$ processes already invoked a valid $\BFTAPPEND(r)$ before it. Thus no new valid $\BFTPROVE(r)$ can be linearized after $\BFTAPPEND(r)^\star$. Hence the set of valid proofs for round $r$ is fixed, and so is $\Winners_r$.
% \end{proof}
% \begin{lemma}[BFT Across rounds]\label{lem:bft-across-rounds}
% For any $r, r'$ such that $r < r'$, if $r'$ is closed, $r$ is also closed.
% \end{lemma}
% \begin{proof}
% Let $r \in \mathcal{R}$. By \cref{def:bft-closed-round}, if $r + 1$ is closed, then for all $\DL[k]$, $r + 1$ is closed in $\Seq^k$. By the implementation, a process can only invoke $\BFTAPPEND(r + 1)$ after observing at least $n - f$ valid $\BFTPROVE(r)$, which means that for all $\DL[k]$, $r$ is closed in $\Seq^k$. Hence by \cref{def:bft-closed-round}, $r$ is closed.
% Because $r$ is monotonically increasing, we can reccursively apply the same argument to conclude that for any $r, r'$ such that $r < r'$, if $r'$ is closed, $r$ is also closed.
% \end{proof}
% \begin{lemma}[BFT Progress]\label{lem:bft_progress}
% For any correct process $p_i$ such that
% \[
% \received \setminus (\delivered \cup (\cup_{r' < r} \cup_{j \in W[r'] \prop[r'][j]})) \neq \emptyset
% \]
% with $r$ the highest closed round in the $\DL$ linearization. Eventually $r+1$ will be closed.
% \end{lemma}
% \begin{lemma}[BFT Winners invariant]\label{lem:bft-winners-invariant}
% For any closed round $r$, define
% \[
% \Winners_r = \{j: \BFTPROVE_j(r) \prec \BFTAPPEND^\star(r)\}
% \]
% called the unique set of winners of round $r$.
% \end{lemma}
% \begin{lemma}[BFT n-f lower-bounded Winners]
% Let $r$ a closed round, $|W[r]| \geq n-f$.
% \end{lemma}
% \begin{remark}\label{rem:correct-in-winners}
% Because we assume $n \geq 2f+ 1$, if $|W[r]| \geq n-f$ at least 1 correct have to be in $W[r]$ to progress.
% \end{remark}
% \begin{lemma}[BFT Winners must purpose]\label{lem:bft-winners-purpose}
% Let $r$ a closed round, for all process $p_j$ such that $j \in W[r]$, $p_j$ must have executed $\RBcast(j, PROP, \_, r)$ and hence any correct will eventually set $\prop[r][j]$ to a non-$\bot$ value.
% \end{lemma}
% \begin{lemma}[BFT Messages Incariant]\label{lem:bft-messages-invariant}
% For any closed round $r$ and any correct process $p_i$ such that $\forall j \in \Winners_r$: $\prop^{(i)}[r][j] \neq \bot$ define
% \[
% \Messages_r = \cup_{j \in \Winners_r} prop^{(i)}[r][j]
% \]
% as the set of messages proposed by the winners of round $r$
% \end{lemma}
% \begin{lemma}[BFT EVentual proposal closure]\label{lem:bft-eventual-proposal-closure}
% If a correct process $p_i$ define $M$ at line~\ref{code:Mcompute}, then for every $j \in \Winners_r$, $\prop^{(i)}[r][j] \neq \bot$.
% \end{lemma}
% \begin{lemma}[BFT Unique proposal per sender per round]\label{lem:bft-unique-proposal}
% For any round $r$ and any process $p_i$, if $p_i$ invokes two $\RBcast$ call for the same round, such that $\RBcast(i, PROP, S, r) \prec \RBcast(i, PROP, S', r)$. Then for any correct process $p_j$, $\prop^{(j)}[r][i] \in \{\bot, S\}$
% \end{lemma}
% \begin{lemma}[BFT $W_r$ as grow only set]\label{lem:bft-wr-grow-only}
% For any correct process $p_i$. If $p_i$ computes $W_r$ at two different times $t_1$ and $t_2$ with $t_1 < t_2$, then $W_r^{t_1} \subseteq W_r^{t_2}$.
% \end{lemma}
% \begin{proof}
% By the implementation, $W_r$ is computed exclusively from the results of $\{j: (j, \PROVEtrace(r)) \in \bigcup_{k \in \Pi} Y[k].\BFTREAD()\}$.
% We know by BFT-READ Anti-Flickering that for any two $\BFTREAD()$ operations $op_1, op_2$ such that $op_1 \prec op_2$, the result of $op_2$ is included in the result of $op_1$. Therefore, if $p_i$ computes $W_r$ at two different times $t_1$ and $t_2$ with $t_1 < t_2$, then $W_r^{t_1} \subseteq W_r^{t_2}$.
% \end{proof}
% \begin{lemma}[BFT well defined winners]\label{lem:bft-well-defined-winners}
% For any closed round $r$, if a correct process $p_i$ compute $W_r$, then $W_r = \Winners_r$ with $|W_r| \geq n - f$.
% \end{lemma}
% \begin{proof}
% By \Cref{lem:bft-read-safety}, any correct process $p_i$ computing $W_r$ after round $r$ is closed includes all valid $\BFTPROVE(r)$ in its computation of $W_r$. Therefore $W_r = \Winners_r$.
% By \Cref{def:bft-closed-round}, at least $n - f$ distinct processes invoked a valid $\BFTAPPEND(r)$ before $\BFTAPPEND(r)^\star$. By the implementation in algorithm D, if a process correct $j$ invoked a valid $\BFTAPPEND(r)$, thats means that he observed at least $n - f$ valid $\BFTPROVE(r)$ submitted by distinct processes. By \Cref{lem:bft-wr-grow-only}, once $p_j$ observed $n - f$ valid $\BFTPROVE(r)$, any correct process computing $W_r$ will eventually observe at least these $n - f$ valid $\BFTPROVE(r)$. By \Cref{lem:bft-stable-round-closure}, no more valid $\BFTPROVE(r)$ can be linearized after round $r$ is closed, so any correct process computing the same fixed set $W_r$ of at least $n - f$ distinct processes.
% \end{proof}
% \begin{lemma}[BFT Non-empty winners proposal]\label{lem:bft-non-empty-winners-proposal}
% For every process $p_i$ such as $i \in W_r$, eventually $\prop[r][i] \neq \bot$.
% \end{lemma}
% \begin{proof}
% By the implementation, if $i \in W_r$, then $(i, \PROVEtrace(r))$ is included in the result of at least one $\BFTREAD()$ operation. Hence there exist a valid $\BFTPROVE(r)$ operation.
% By \Cref{lem:bft-prove-validity}, this implies that there exist at least $f + 1$ valid $\PROVE(r)$ operation invoked by processes. At least one of these processes is correct, say $p_j$. By the implementation, $p_j$ invoked $\BFTPROVE(r)$ after receiving a $Rdeliver(j, \texttt{PROP}, S, r)$ message from $p_i$. Therefore, by the reliable broadcast properties, the message will eventually be delivered to every correct process, hence eventually for any correct process $\prop[r][i] \neq \bot$.
% \end{proof}
% \begin{definition}[BFT Message invariant]\label{def:bft-message-invariant}
% For any closed round $r$, for any correct process $p_i$, such that $\nexists j \in W_r : \prop[r][j] = \bot$, twe define the set
% \[
% \Messages_r = \bigcup_{j \in \Winners_r} \prop[r][j]
% \]
% as the unique set of messages proposed during round $r$.
% \end{definition}
% \begin{lemma}[BFT Proposal convergence]\label{lem:bft-proposal-convergence}
% For any closed round $r$, for any correct process $p_i$, that define $M_r$ at line B10, we have $M_r = \Messages_r$.
% \end{lemma}
% \begin{proof}
% By \Cref{lem:bft-well-defined-winners}, any correct process $p_i$ computing $W_r$ after round $r$ is closed has $W_r = \Winners_r$.
% By \Cref{lem:bft-non-empty-winners-proposal}, for any correct process $p_i$, such as $i \in W_r$, eventually $\prop[r][i] \neq \bot$.
% Therefore, eventually for any correct process $p_i$, at line B10 we have
% \[
% M_r = \bigcup_{j \in W_r} \prop[r][j] = \bigcup_{j \in \Winners_r} \prop[r][j] = \Messages_r
% \]
% \end{proof}
% \begin{lemma}[BFT Inclusion]\label{proof:bft-inclusion}
% If a correct process $p_i$ ABroadcasts a message $m$, then eventually any correct process $p_j$ ADelivers $m$.
% \end{lemma}
% \begin{proof}
% Let $m$ be a message ABroadcast by a correct process $p_i$ and eventually exit the \texttt{ABroadcast} function at line A10.
% By the implementation, if $p_i$ exits the \texttt{ABroadcast} function at line A10, then there exists a round $r'$ such that $m \in \prop[r'][j]$ for some $j \in W_{r'}$.
% Since $p_i$ is correct, seeing that $m \in \prop[r'][j]$ for some $j \in W_{r'}$ implies that $p_i$ received a $Rdeliver(j, \texttt{PROP}, S, r')$ message from $p_j$ such that $m \in S$. And because $p_j$ is in $W_{r'}$, at least $n - f$ correct processes invoked a valid $Y[j].\BFTPROVE(r')$ before the round $r'$ were closed. By the reliable broadcast properties, the $Rdeliver(j, \texttt{PROP}, S, r')$ message will eventually be delivered to every correct process, hence eventually for any correct process $m \in \prop[r'][j]$ with $j \in W_{r'}$. Hence $m$ will eventually be included in the set $\Messages_{r'}$ defined in \Cref{def:bft-message-invariant} and thus eventually be ADelivered by any correct process.
% \end{proof}
\subsection{Correctness Lemmas}
\begin{definition}[Closed Round]
A round $r \in \mathcal{R}$ is said to be \emph{closed} for a correct process $p_i$ if at the moment $p_i$ computes $\winners[r]$, it satisfies $|\{k : (k, r) \in \BFTREAD()\}| \geq n - t$.
\end{definition}
\begin{lemma}[Round Monotonicity]\label{lem:round-monotonicity}
If a round $r$ is closed, then every round $r_1 < r$ is also closed.
\end{lemma}
\begin{proof}
\textbf{Base:} $r = 0$. Suppose round $1$ is closed, the set $\{r' \in \mathcal{R}: r' < r\}$ is empty, so the claim holds.
\textbf{Inductive step:} Let $r \geq 1$. Assume that the property holds for all rounds $r' < r$: whenever round $r'$ is closed, all rounds $r_2 < r'$ are also closed. We show that if round $r$ is closed, then all rounds $r_1 < r$ are closed.
Suppose round $r$ is closed. This means at least one correct process $p_i$ has reached line \ref{alg:check-validated} and satisfied the condition $|\validated(r)| \geq n - t$. Consequently, $p_i$ has invoked $\BFTAPPEND(\langle j, r \rangle)$ for each $j \in \Pi$ at line \ref{alg:append}. Since these operations are invoked by a correct process, and they depend on valid proofs in the byzantine fault tolerant deny list, at least one of these operations must have succeeded in the DL object.
Moreover, by the algorithm structure, a correct process can only reach the beginning of round $r$ after completing round $r-1$. In particular, process $p_i$ reaches line \ref{alg:main-loop} for round $r$ only after having completed round $r-1$, which requires the process to have observed at least $|\done[r-1]| \geq n - t$ (line \ref{alg:check-done} for round $r-1$). This condition can only be satisfied if round $r-1$ is closed: at least $n - t$ processes must have issued DONE messages, and since $n > 3f$, at least one of these is correct.
Since $n - t > 2f + 1$, among the $n - t$ processes satisfying the condition for round $r-1$, at least one is correct. A correct process that issued a DONE message for round $r-1$ must have previously completed its execution of lines \ref{alg:append} for round $r-1$, which in turn required observing $|\validated(r-1)| \geq n - t$ from line \ref{alg:check-validated}. Thus, round $r-1$ is closed.
Now, considering any round $r_1 < r-1$: by the inductive hypothesis applied to round $r-1$, since round $r-1$ is closed and $r_1 < r-1$, we have that $r_1$ is also closed.
By strong induction, if round $r$ is closed, all rounds $r_1 < r$ are closed.
\end{proof}
\begin{lemma}[Uniqueness of Winners' Proposals]\label{lem:bft-unique-proposal}
For any closed round $r$ and any process $p_j \in \winners[r]$, there exists a unique set $S_j \subseteq \mathcal{M}$ such that every correct process $p_i$ that has received a reliable delivery of a $\texttt{PROP}$ message from $p_j$ for round $r$ receives exactly this set $S_j$.
\end{lemma}
\begin{proof}
Let $r$ be a closed round and $p_j \in \winners[r]$. Since $j \in \winners[r]$, it means that $(j, r) \in \BFTREAD()$, i.e., at least $t+1$ distinct processes have invoked a valid $\BFTPROVE(\langle j, r \rangle)$ before the round $r$ closed.
By the algorithm, a correct process $p_i$ invokes $\BFTPROVE(\langle j, r \rangle)$ only upon receiving a reliable delivery of a $\texttt{PROP}$ message from $p_j$ for round $r$ at line \ref{alg:append}. Let $S_j^{(i)}$ denote the set received by $p_i$.
Since at least $t+1$ distinct processes have performed a valid $\BFTPROVE(\langle j, r \rangle)$, and since $t < n/3$, at least one of these processes is correct. Thus, at least one correct process must have received a reliable broadcast from $p_j$ for round $r$.
Now, by Bracha's Byzantine Reliable Broadcast specification, for any message broadcast instance by process $p_j$ in round $r$, all correct processes that deliver this broadcast either receive the identical message or none at all. Formally, for all correct processes $p_i, p_i'$ that received a delivery from $p_j$ for round $r$, we have $S_j^{(i)} = S_j^{(i')}$.
Therefore, there exists a unique set $S_j$ such that every correct process $p_i$ that receives a reliable delivery from $p_j$ for round $r$ receives exactly $S_j$.
\end{proof}
\begin{lemma}[Winners Stability]\label{lem:winners-stability}
For any closed round $r$, the set $\winners[r]$ is stable.
\end{lemma}
\begin{proof}
Let $r$ be a closed round. By definition, a closed round $r$ means that at least one correct process $p_i$ has observed $|\{k : (k, r) \in \BFTREAD()\}| \geq n - t$ and computed $\winners[r]$ at line \ref{alg:check-done}.
When round $r$ becomes closed, this implies that at least $n - t$ distinct processes have invoked $\BFTAPPEND(\langle j, r \rangle)$ for $j \in \Pi$ (by the algorithm structure, since $\done[r]$ contains DONE messages from processes that completed line \ref{alg:append}). Since $n > 3f$, we have $n - t > 2f + 1 > t + 1$.
Consider a fixed $j \in \Pi$. Since at least $n - t > t + 1$ processes have invoked a valid $\BFTAPPEND(\langle j, r \rangle)$, by \cref{lem:bft-prove-validity}, any subsequent invocation of $\BFTPROVE(\langle j, r \rangle)$ will be invalid.
By \cref{lem:bft-prove-anti-flickering}, once a $\BFTPROVE(\langle j, r \rangle)$ operation becomes invalid, all subsequent $\BFTPROVE(\langle j, r \rangle)$ operations are also invalid.
This holds for all $j \in \Pi$. Therefore, after the round $r$ is closed, the set of valid $\BFTPROVE(\langle j, r \rangle)$ operations for each $j$ cannot grow. By \cref{lem:bft-read-anti-flickering}, any subsequent $\BFTREAD()$ invocation will not return any new $(k, r)$ pairs beyond those already returned. Thus, $\winners[r] = \{j : (j, r) \in \BFTREAD()\}$ becomes stable and cannot change.
Since this reasoning applies to all correct processes that compute $\winners[r]$ after round $r$ is closed, all correct processes will compute the same stable set $\winners[r]$.
\end{proof}
\begin{lemma}[Message Content Invariance]\label{lem:message-content-invariance}
For any closed round $r$ and any correct process $p_i$, the set $M$ computed at line \ref{code:Mcompute} by $p_i$ is identical to the set computed by any other correct process $p_j$ for the same round $r$.
\end{lemma}
\begin{proof}
Let $r$ be a closed round and let $p_i, p_{i'}$ be two correct processes. By the algorithm, both processes compute $M$ as:
\[
M^{(i)} = \bigcup_{j \in \winners[r]} \prop^{(i)}[r][j]
\]
and
\[
M^{(i')} = \bigcup_{j \in \winners[r]} \prop^{(i')}[r][j]
\]
at line \ref{code:Mcompute}.
By \cref{lem:winners-stability}, the set $\winners[r]$ is stable once round $r$ is closed. Therefore, both $p_i$ and $p_{i'}$ compute the same set of winners $\winners[r]$.
Now, consider any winner $j \in \winners[r]$. By \cref{lem:bft-unique-proposal}, there exists a unique set $S_j \subseteq \mathcal{M}$ such that every correct process that receives a reliable delivery of a $\texttt{PROP}$ message from $p_j$ for round $r$ receives exactly $S_j$.
By the algorithm, each correct process stores this received set in its local variable: $\prop^{(i)}[r][j] = S_j$ and $\prop^{(i')}[r][j] = S_j$.
Since both processes compute the union over the same set of winners, and each winner's proposal is identical for all correct processes:
\[
M^{(i)} = \bigcup_{j \in \winners[r]} \prop^{(i)}[r][j] = \bigcup_{j \in \winners[r]} S_j = \bigcup_{j \in \winners[r]} \prop^{(i')}[r][j] = M^{(i')}
\]
Therefore, all correct processes compute the same set $M$ for any closed round $r$.
\end{proof}
\begin{lemma}[Inclusion]\label{lem:bft-inclusion}
If a correct process $p_i$ invokes $\ABbroadcast(m)$, then there exist a closed round $r$ and a winner $j \in \winners[r]$ such that $p_j$ invoked $\RBcast(j, \texttt{PROP}, S, r)$ with $m \in S$.
\end{lemma}
\begin{proof}
Let $p_i$ be a correct process that invokes $\ABbroadcast(m)$. By the algorithm, $p_i$ adds $m$ to $\unordered$. Consequently, $\unordered \setminus \ordered \neq \emptyset$, and the process enters the main loop and eventually invokes $\RBcast(i, \texttt{PROP}, S_i^{(1)}, r_1)$ for some round $r_1$ where $m \in S_i^{(1)}$.
We distinguish two cases:
\textbf{Case 1: $p_i$ becomes a winner in round $r_1$.}
If $p_i$ is elected as a winner for round $r_1$ (i.e., $i \in \winners[r_1]$), then the claim holds with $r = r_1$ and $j = i$.
\textbf{Case 2: $p_i$ does not become a winner in round $r_1$.}
If $p_i$ is not elected as a winner, by the properties of Reliable Broadcast (Bracha's specification), at least one correct process $p_{i_1}$ will eventually receive the reliable delivery of the $\texttt{PROP}$ message from $p_i$ for round $r_1$. Process $p_{i_1}$ adds all messages from $S_i^{(1)}$ to its $\unordered$ set at line \ref{alg:append}. In particular, $m$ is now in $p_{i_1}$'s $\unordered$ set.
In round $r_2 > r_1$ (and any subsequent round), process $p_{i_1}$ computes $S_{i_1}^{(2)} = \unordered \setminus \ordered$ and invokes $\RBcast(i_1, \texttt{PROP}, S_{i_1}^{(2)}, r_2)$ with $m \in S_{i_1}^{(2)}$.
This process repeats: either $p_{i_1}$ becomes a winner and the claim holds, or another correct process receives $p_{i_1}$'s proposal and includes $m$ in its own proposal.
Since $n > 3f$, we have $n - t > t + 1 > f$. By the pigeonhole principle, there eventually exists a round $r$ where at least $n - t$ distinct processes have proposed sets containing $m$. Since more than $2f$ processes have proposed $m$, at least one of them must be correct and be elected as a winner. Therefore, there exist a round $r$ and a winner $j \in \winners[r]$ such that $m \in S_j$ was broadcast by $p_j$.
\end{proof}
\begin{lemma}[Eventual Closure]\label{lem:bft-eventual-closure}
For any correct process $p_i$, if $\unordered \setminus \ordered \neq \emptyset$ and if $r$ is the highest closed round observed by $p_i$, then eventually round $r+1$ will be closed with $|\winners[r+1]| \geq n - t$.
\end{lemma}
\begin{proof}
Let $p_i$ be a correct process such that $\unordered \setminus \ordered \neq \emptyset$ after round $r$ is the highest closed round it observed. By the main loop of Algorithm~\ref{alg:bft-arb}, $p_i$ eventually enters round $r+1$, computes $S=\unordered\setminus\ordered$, and invokes $\RBcast(\texttt{PROP},S,\langle i,r+1\rangle)$.
By RB Validity, every correct process eventually $\rdeliver(\texttt{PROP},S,\langle i,r+1\rangle)$. Upon this delivery, each correct process executes $\BFTPROVE(\langle i,r+1\rangle)$. Hence at least $n-t$ correct processes issue a proof for candidate $i$ in round $r+1$, and in particular the threshold $t+1$ used in $\validated(r+1)$ is eventually met for that candidate.
The same argument applies to each correct process that broadcasts in round $r+1$: once its proposal is RB-delivered, at least $n-t$ correct processes issue the corresponding proofs, so that sender is eventually included in $\validated(r+1)$. Since there are at least $n-t$ correct processes, eventually $|\validated(r+1)| \geq n-t$, and the wait at line~\ref{alg:check-validated} is eventually released for every correct process in that round.
After this point, each correct process executes the $\BFTAPPEND$ loop (line~\ref{alg:append}) and sends $\texttt{DONE}$ to all processes. By reliability of point-to-point channels, every correct process eventually receives at least $n-t$ DONE messages, so the wait at line~\ref{alg:check-done} is also eventually released. At that moment, the process computes $\winners[r+1] \gets \validated(r+1)$, and by the previous bound we have $|\winners[r+1]| \geq n-t$.
Therefore round $r+1$ eventually becomes closed with at least $n-t$ winners.
\end{proof}
\begin{lemma}[Total Order]\label{lem:bft-total-order}
For any two correct processes $p_i$ and $p_j$, the sequence $\ordered$ maintained locally by $p_i$ and the sequence maintained by $p_j$ contain the same messages in the same order, provided that both have reached the same set of closed rounds.
\end{lemma}
\begin{proof}
We prove the claim by induction on the number of closed rounds completed by both processes.
\textbf{Base case.} Before any closed round is completed, both local sequences are initialized to $\epsilon$, hence identical.
\textbf{Induction step.} Assume that after all closed rounds up to $r-1$, processes $p_i$ and $p_j$ have identical $\ordered$ prefixes. Consider round $r$.
By \Cref{lem:winners-stability}, once round $r$ is closed, both processes use the same stable winner set $\winners[r]$. By \Cref{lem:message-content-invariance}, the set $M$ computed at line~\ref{code:Mcompute} is identical at all correct processes for that round. Both processes then apply the same deterministic ordering function $\order(M)$ and append that same ordered block to their current sequence.
Since they started round $r$ from identical prefixes and append the same ordered suffix for round $r$, their resulting sequences after round $r$ are identical. The induction concludes that for any common set of closed rounds, both correct processes maintain the same messages in the same order.
\end{proof}
\begin{theorem}
The algorithm implements a BFT Atomic Reliable Broadcast.
\end{theorem}

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\documentclass{beamer}
\usetheme{Boadilla}
\usecolortheme{orchid}
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\usepackage{tikz}
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\title{Amaury JOLY - Winter School GDR Cybersécurité}
\author{Amaury JOLY}
\institute{Université Aix-Marseille \\ Laboratoire d'Informatique et Systèmes (LIS)}
\date{Janvier 2026}
\begin{document}
\begin{frame}
\titlepage
\vspace{-1.2em}
\begin{center}
\includegraphics[height=1cm]{images/logoamu}\hspace{1cm}%
\includegraphics[height=1.5cm]{images/logolis}\hspace{1cm}
\includegraphics[height=0.9cm]{images/logodalgo}\hspace{1cm}%
\includegraphics[height=0.6cm]{images/logoparsec}
\end{center}
\end{frame}
\begin{frame}{Who am I?}
\begin{itemize}
\item \textbf{Amaury JOLY}
\item 3rd-year PhD candidate at the \textbf{Laboratory of Informatics and Systems (LIS)}
\item \textbf{Distributed Algorithms} team
\item Supervised by \textbf{Emmanuel GODARD} and \textbf{Corentin TRAVERS}
\item \textbf{CIFRE} PhD with the company \textbf{Parsec}
\end{itemize}
\end{frame}
%------------------------------------------------------------
\begin{frame}{Parsec: company \& product}
\begin{itemize}
\item \textbf{Parsec} develops an end-to-end encrypted file sharing platform
\item Client--server solution: users collaborate through shared workspaces
\item \textbf{End-to-end encryption}: the server only sees \emph{ciphertexts}
\item \textbf{Distributed PKI management among clients} (keys/identities handled at the edge)
\item \alert{one central server stores encrypted data and redistributes it to clients}
\end{itemize}
\end{frame}
%------------------------------------------------------------
\begin{frame}{My topic (high level)}
\begin{block}{Problem statement}
\textit{``Weak consistency in a zero-trust cloud for real-time collaborative applications.''}
\end{block}
\vspace{0.4em}
\begin{itemize}
\item Real-time collaboration: concurrent updates, low latency, intermittent connectivity
\item We want \textbf{weak consistency} (e.g., eventual / causal behaviors) with clear semantics under concurrency
\item \textbf{Zero-trust cloud} (Parsec-like setting):
\begin{itemize}
\item central server trusted for \textbf{availability} only
\item server can be \textbf{honest-but-curious} (observes metadata, stores/forwards ciphertexts)
\item \textbf{no trust assumptions on clients} (they may be compromised or mutually distrustful)
\end{itemize}
\end{itemize}
\end{frame}
\begin{frame}
\frametitle{Our Model}
\begin{block}{Assumptions}
\begin{itemize}
\item The system is highly connected
\item The system is not partitionable
\item The system is asynchronous (i.e., no assumption on message delays or relative process speeds)
\item Nodes can fail by \textbf{crash} (i.e., stop functioning)
\item Nodes can be \textbf{Byzantine} (i.e., arbitrary behavior)
\item The communication network is reliable but byzantine nodes can delay or reorder messages
\item There is a Reliable Broadcast abstraction available
\end{itemize}
\end{block}
\end{frame}
\begin{frame}
\frametitle{Consistency classes}
\begin{columns}
\column{0.5\textwidth}
\resizebox{\columnwidth}{!}{
\includegraphics{images/carte_criteres.png}
}
\column{0.5\textwidth}
One approach to define the consistency of an algorithm is to place the concurrent history it produces into a consistency class. \\
We can define 3 consistency classes:
\begin{itemize}
\item \textbf{State Locality} (LS)
\item \textbf{Validity} (V)
\item \textbf{Eventual Consistency} (EC)
\end{itemize}
\end{columns}
\end{frame}
\begin{frame}
\frametitle{State Locality (LS)}
\begin{columns}
\column{0.4\textwidth}
\include{localiteetat_hc}
\column{0.6\textwidth}
\begin{block}{Definition}
For every process $p$, there exists a linearization containing all of $p$'s read operations. \\
\end{block}
\begin{math}
\begin{array}{ll}
e.g.: & \textcolor{blue}{C_{p_1} = \{r/(0,0), r/(0,2)^w, w(2)\}}, \\
& \textcolor{red}{C_{p_2} = \{r/(0,0), r/(0,1)^w, w(1)\}}, \\
& \textcolor{blue}{r/(0,0) \bullet w(2) \bullet r/(0,2)^w} \\
& \textcolor{red}{r/(0,0) \bullet w(1) \bullet r/(0,1)^w} \\
\end{array}
\end{math}
\end{columns}
\begin{flushright}
\begin{math}
LS = \left\{
\begin{array}{l}
\mathcal{T} \rightarrow \mathcal{P}(\mathcal{H}) \\
T \rightarrow \left\{
\begin{tabular}{lll}
$H \in \mathcal{H}:$ & \multicolumn{2}{l}{$\forall p \in \mathcal{P}_H, \exists C_p \subset E_H,$} \\
& & $\hat{Q}_{T,H} \subset C_p$ \\
& $\land$ & $lin(H[p \cap C_p / C_p]) \cap L(T) \neq \emptyset$ \\
\end{tabular}
\right. \\
\end{array}
\right.
\end{math}
\end{flushright}
\end{frame}
\begin{frame}
\frametitle{Validity (V)}
\begin{columns}
\column{0.4\textwidth}
\include{validite_hc}
\column{0.6\textwidth}
\begin{block}{Definition}
There exists a co-finite set of events such that for each of them, a linearization of all write operations justifies them. \\
\end{block}
\begin{math}
\begin{array}{ll}
e.g.: & E' = \{r/(2,1)^w, r/(1,2)^w\} \\
& w(2) \bullet w(1) \bullet \textcolor{red}{r/(2,1)^w} \\
& w(1) \bullet w(2) \bullet \textcolor{red}{r/(1,2)^w} \\
\end{array}
\end{math}
\end{columns}
\begin{flushright}
\begin{math}
V = \left\{
\begin{array}{l}
\mathcal{T} \rightarrow \mathcal{P}(\mathcal{H}) \\
T \rightarrow \left\{
\begin{array}{lll}
H \in \mathcal{H}: & \multicolumn{2}{l}{|U_{T,H}| = \infty} \\
& \lor & \exists E' \subset E_H, (|E_H \setminus E'| < \infty \\
& & \land \forall e \in E', lin(H[E_H / {e}]) \cap L(T) \neq \emptyset) \\
\end{array}
\right. \\
\end{array}
\right.
\end{math}
\end{flushright}
\end{frame}
\begin{frame}
\frametitle{Eventual Consistency (EC)}
\begin{columns}
\column{0.4\textwidth}
\include{convergence_hc}%
\column{0.5\textwidth}
\begin{block}{Definition}
There exists a co-finite set of events such that for each of them, a single linearization justifies them. \\
\end{block}
\begin{math}
\begin{array}{ll}
e.g.: & E' = \{r/(1,2)^w, r/(1,2)^w\} \\
& w(1) \bullet w(2) \bullet \textcolor{red}{r/(1,2)^w} \\
\end{array}
\end{math}
\end{columns}
\begin{flushright}
\begin{math}
EC = \left\{
\begin{array}{l}
\mathcal{T} \rightarrow \mathcal{P}(\mathcal{H}) \\
T \rightarrow \left\{
\begin{array}{lll}
H \in \mathcal{H}: & \multicolumn{2}{l}{|U_{T,H}| = \infty} \\
& \lor & \exists E' \subset E_H, |E_H \setminus E'| < \infty \\
& & \land \displaystyle\bigcap_{e \in E'} \delta_T^{-1}(\lambda(e)) \neq \emptyset \\
\end{array}
\right. \\
\end{array}
\right.
\end{math}
\end{flushright}
\end{frame}
\begin{frame}{Main Work}
\begin{itemize}
\item We designed a distributed algorithm that use a \textbf{byzantine-tolerant eventually consistent register} in our model to achieve Agreement with $t < n/3$ Byzantine nodes.
\item I'm working on a framework using this algorithm to build collaborative applications for the context of a zero-trust cloud.
\end{itemize}
\end{frame}
\begin{frame}
\frametitle{Thank you for your attention!}
\vfill
\begin{center}
\includegraphics[height=1cm]{images/logoamu}\hspace{1cm}%
\vspace{1em}
\includegraphics[height=1.5cm]{images/logolis}\hspace{1cm}%
\vspace{1em}
\includegraphics[height=0.9cm]{images/logodalgo}\hspace{1cm}%
\vspace{1em}
\includegraphics[height=0.6cm]{images/logoparsec}
\end{center}
\end{frame}
\end{document}

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