Papers for

distributed system operations teams

Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.

Selective silence attacks disrupt blockchain consensus and how to detect them

Vigil: Accountable Liveness against Selective Silence

Abstract: BFT accountability is well understood for safety violations, and recent work attributes global liveness violations; \emph{recipient-selective} silence remains unresolved. A selectively silent adversary withholds messages from some honest nodes while behaving correctly toward others. It can stall consensus yet evade every existing mechanism. We initiate a systematic study of accountability against selective silence. Negatively, a lone attacker silent toward at most $f$ honest nodes is indistinguishable from an honest node, yielding a universal lower bound $K_{\mathrm{SI}} \ge f{+}1$ on the \emph{silence identification threshold}; moreover, any feedback-free repair after a silence-induced violation costs $Θ(n^3)$. Positively, \textsc{Vigil}, a Tendermint variant, matches these bounds with attack-adaptive forwarding, via bitmap cross-attestation, core-based membership, and challenge--response auditing. It pays $O(n)$ authenticators per node when no selective silence occurs (plus $Θ(n^2)$ bitmap metadata bits per node), relays in proportion to the attack's width (sub-threshold silence can force up to $n^3/27$ relays per view, a cost we price exactly), and majority-accuses any node silent toward more than a tunable resilience $τ_A$ of honest peers ($K_{\mathrm{SI}} = τ_A{+}1$, optimal at $τ_A = f$). We also price the residual sub-threshold griefing surface exactly and extend identification to $x$-partial synchrony. Real-network experiments on a three-region WAN, together with a simulator held to exact equality with every closed form, confirm each threshold and cost: at $2\%$ loss, an $f{+}1$ accusation bar falsely accuses $91.2\%$ of honest nodes, while our majority bar accuses $0.002\%$.

Wed 16 SeptDistributed, Parallel, and Cluster Computing
The gist
In blockchain systems that need many computers to agree, some bad actors can quietly ignore certain honest participants without being easily caught. The authors studied how to detect these ‘selective silence’ attacks that can freeze progress. They prove limits on how well anyone can identify such attackers, then create a system called Vigil that detects and limits these hidden attacks efficiently. Tests on real networks show Vigil reduces false accusations while catching real misbehavior.
Open → 2609.18778v1