Karim Eldefrawy

Cryptography, Cybersecurity, Privacy

Co-founder and CTO at Confidencial.io
2017-2021: SRI
2011-2016: HRL Laboratories
2006-2010: PhD@UC Irvine

Scientific curiosity

Scientific knowledge map · Paper #36

Brief Announcement: Secure Self-Stabilizing Computation

Shlomi Dolev, Karim Eldefrawy, Juan A. Garay, Muni Venkateswarlu Kumaramangalam, Rafail Ostrovsky, and Moti Yung

2017 · ACM Symposium on Principles of Distributed Computing (PODC)

  • Theory
  • protocol
  • algorithm

What does the paper try to establish?

Can a continuously running distributed computation automatically recover not only functional consistency but also input, output, and state confidentiality and computational correctness after a temporary period in which every party may have been compromised?

What is the proposed answer?

The announcement defines secure self-stabilizing computation and sketches an FSM protocol that repeatedly establishes fresh keys, validates secret-shared state through MPC and error correction, resets invalid state to a default, and securely computes the next transition and output. Once independent recovery restores the required Byzantine threshold, the construction is intended to converge to consistent private computation and progressively erase the adversary's knowledge of current state.

Six dimensions, kept separate

The chart summarizes documented evidence and process. It is not a correctness probability, confidence score, or ranking, and no composite score is calculated.

The visual spider chart requires JavaScript. The complete values and rationales follow in text.

LowMediumHighN/A = not assessed

A smaller value means less documented support for that dimension, not that the paper is false or unimportant.

Epistemic evidence Medium

The complete brief specifies the model, recovery concept, component pipeline, FSM algorithm, threshold example, and forgetting intuition. Its three pages do not include formal security definitions and proofs, an implementation, or experiments, so the evidence remains Medium.

Convergence, closure, MPC security, and secure self-stabilization Clock, key, VSS, state-validation, transition, and output pipeline Secure self-stabilizing FSM Algorithm 1
Auditability High

A checked-in author copy with SHA-256, page count, and precise page anchors, plus the official DOI, makes every claim in the brief directly inspectable. No extended artifact was located.

Secure self-stabilization problem and claimed direction Official PODC publication identity
Production provenance Medium

Named authorship, affiliations, funding acknowledgments, date, venue, DOI, and author copy are documented. Contributor roles, revision history, tool use, and any extended-version lineage have not been audited.

Secure self-stabilization problem and claimed direction Official PODC publication identity
External scrutiny Medium

PODC publication establishes external venue scrutiny, but the item is a brief announcement and no review reports, rebuttal, independent proof audit, implementation, or reproduction were located.

Official PODC publication identity
Reception Low

OpenAlex reported 5 citations on 2026-07-11. Under the author-defined corpus rule, 0 through 8 located citations is Low. The count is index- and date-dependent and is not evidence of correctness.

Dated citation-count snapshot
Contribution significance Medium

The brief articulates a distinctive recovery target that combines confidentiality, correctness, and self-stabilization and supplies a concrete FSM composition. Priority, generality, and downstream adoption require a broader literature audit.

Secure self-stabilization problem and claimed direction Convergence, closure, MPC security, and secure self-stabilization

Assessment: Ai draft author review pending · 2026-07-11 · rubric 0.2. These dimensions describe documented support and process, not truth, correctness, or a universal ranking. No composite score is calculated.

Hierarchical knowledge map

Collapse a branch for a top-level reading, or follow its source links and child nodes to audit the evidence and boundaries underneath it.

paper

Brief Announcement: Secure Self-Stabilizing Computation

A three-page announcement that joins self-stabilizing distributed systems with secure MPC so a computation can recover confidentiality and correctness after total but temporary compromise.

Secure self-stabilization problem and claimed direction
  1. scope Continuous distributed FSM model defined

    n parties over a complete synchronous or semi-synchronous network continuously compute a public Mealy FSM on periodically supplied secret-shared inputs. Parties do not know their compromise history and maintain secret shares of FSM state and output.

    Parties, network, key setup, hardware, inputs, and clocks Clock, key, VSS, state-validation, transition, and output pipeline
    1. assumption

      Cryptographic and hardware setup

      assumed

      Every party has a true random number generator and tamper-resistant access to its private key and the configuration authority's public key; parties can authenticate fresh public keys, derive pairwise secure channels, and establish secure broadcast.

      Parties, network, key setup, hardware, inputs, and clocks
    2. threat model

      Temporary total mixed compromise

      defined

      A computationally bounded adversary may passively or actively corrupt any number of parties, including all n for a finite interval, but watchdog-driven recovery prevents indefinite control of every party and the adversary cannot immediately recapture a just-recovered party.

      Mixed mobile adversary and recovery assumptions
  2. definition

    Security recovery requirement

    introduced

    Secure self-stabilization extends functional convergence so that after enough parties recover and the MPC corruption threshold again holds, secrecy of computation state, inputs, and outputs and correctness of computation are automatically regained.

    Convergence, closure, MPC security, and secure self-stabilization
  3. protocol Secure FSM stabilization protocol specified at brief level

    Each transition round refreshes communication keys, verifiably reshapes the state shares, securely checks that they encode a legitimate state, and evaluates public transition and output circuits using an existing MPC protocol.

    Clock, key, VSS, state-validation, transition, and output pipeline
    1. algorithm

      Private transition and output evaluation

      specified

      On a valid state, MPC applies transition circuit T to the current state and new input and output circuit O to produce secret-shared next state and output; after reset, the same circuits run from S0.

      Secure self-stabilizing FSM Algorithm 1
  4. claim group Stated recovery claims source asserted

    The brief states conditional recovery rather than uninterrupted security: during total compromise all secrets may be exposed, and protection resumes only after the required party threshold and supporting services recover.

    Convergence, closure, MPC security, and secure self-stabilization Post-convergence secrecy recovery under transition-graph conditions
    1. claim

      Loss of stale adversarial state knowledge

      graph conditional

      With unknown fresh inputs, a complete FSM transition graph makes every state possible to the adversary after the first post-convergence transition; an expander transition graph is stated to erase state knowledge after logarithmically many transitions.

      Post-convergence secrecy recovery under transition-graph conditions
  5. evidence group Evidence and proof boundary bounded by brief announcement

    The announcement defines the setting, composes known cryptographic and stabilization components, and supplies Algorithm 1 and recovery intuition. It does not present a formal ideal functionality, simulator, theorem statement, full proof, implementation, or experiment.

    Parties, network, key setup, hardware, inputs, and clocks Convergence, closure, MPC security, and secure self-stabilization Secure self-stabilizing FSM Algorithm 1
  6. limitation group Assumptions and limitations material

    Recovery depends on trustworthy local reset, TRNGs, secure hardware keys, clock stabilization, Byzantine agreement, VSS, and an MPC whose threshold has recovered. The protocol does not protect secrets already learned during total compromise or guarantee correct outputs before convergence.

    Parties, network, key setup, hardware, inputs, and clocks Mixed mobile adversary and recovery assumptions Convergence, closure, MPC security, and secure self-stabilization
  7. scrutiny

    External scrutiny

    venue reviewed

    The work appeared as a PODC brief announcement. This gives venue exposure but not the evidentiary weight of a full-paper security proof, independently verified implementation, or public review record.

    Official PODC publication identity

Source index

Locators state the depth of the current audit. PDF page numbers, where present, are one-based file pages; metadata-, summary-, and abstract-bounded records explicitly identify their limitations.

  1. Secure self-stabilization problem and claimed direction Abstract, PDF page 1
  2. Parties, network, key setup, hardware, inputs, and clocks Section 1, System and Network Model, PDF pages 1-2
  3. Mixed mobile adversary and recovery assumptions Section 1, Mixed Adversarial Model, PDF page 2
  4. Convergence, closure, MPC security, and secure self-stabilization Section 2, PDF page 2
  5. Clock, key, VSS, state-validation, transition, and output pipeline Section 3, PDF page 3
  6. Secure self-stabilizing FSM Algorithm 1 Algorithm 1, PDF page 3
  7. Post-convergence secrecy recovery under transition-graph conditions Discussion following Algorithm 1, PDF page 3
  8. Official PODC publication identity PODC 2017, pages 415-417, DOI 10.1145/3087801.3087864
  9. Dated citation-count snapshot OpenAlex reported 5 citing works when accessed 2026-07-11