Themis Consensus Extension v1: MEV Mitigation by Randomized Delayed Execution and Intent-Hiding Transactions in Application-Specific Blockchains

• URL: http://arxiv.org/abs/2607.21406v1
• Date: Thu, 23 Jul 2026 15:05:09 GMT
• Title: Themis Consensus Extension v1: MEV Mitigation by Randomized Delayed Execution and Intent-Hiding Transactions in Application-Specific Blockchains
• Abstract summary: We analyze the Themis Consensus Extension v1, first published by Mangata in 2021.<n>The design separates value extraction by reordering from value extraction by denial.<n>We analyze probabilistic extraction, spam, dependent transactions, decryption liveness, session boundaries, total denial, and threshold coalitions.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Maximal extractable value (MEV) arises when privileged participants select, exclude, insert, or reorder pending transactions for private gain. We specify and analyze the Themis Consensus Extension v1, first published by Mangata in 2021. The design separates value extraction by reordering (VER) from value extraction by denial (VED). For VER, block construction and execution occur across consecutive producers: one producer commits a transaction set, and the next derives a publicly verifiable, deterministic, previously un- predictable seed and executes a seed-determined, dependency-preserving permutation. For selective VED, a user may encrypt a transaction for a designated builder and executor. The builder removes an outer layer and commits the opaque inner ciphertext; the executor reveals and executes the plaintext only after commitment. Under selfish but non-colluding validators, an adversary below the underlying consensus fault threshold, secure cryptography, and accountable role performance, the construction limits unilateral post-commit ordering control and hides transaction intent from relays and the builder. It does not provide send-order or receive-order fairness, complete censorship resistance, resistance to builder-executor collusion, or per-transaction price guarantees. We analyze probabilistic extraction, spam, dependent transactions, decryption liveness, session boundaries, total denial, and threshold coalitions. We also document the initial Aura-based Substrate implementation and its subsequent transition to a BABE-based sr25519/VRF seed path, together with delayed execution, Fisher-Yates shuffling, and Xoshiro256++. The result preserves the original proposal while narrowing its claims to explicit assumptions.

Related papers

• RAPTOR: Role-Aware Private Training for Mixture-of-Experts [68.5626338219096]
  RAPTOR is a Role-Aware Private Training framework.<n>RAPTOR alternates shared and expert optimization and targets each failure directly.<n> Experiments on Switch Transformer and OLMoE fine-tuning across GLUE tasks, and on DeepSeek-VL2-Tiny, show consistent gains over standard DP baselines.
  arXiv  Detail & Related papers  (2026-09-04T23:16:12Z)
• ResiSpec: Enhancing Multi-Candidate Speculative Sampling via Residual Distribution Shaping [79.1905186547363]
  ResiSpec is a framework that strategically reforms the proposal distribution during verification.<n>It prevents candidate obsolescence and achieves up to 1.92$times$ speedup over state-of-the-art multi-candidate methods.
  arXiv  Detail & Related papers  (2026-08-25T11:25:55Z)
• When Collaboration Becomes a Trigger: Collective Evidence-Threshold Backdoors in Multi-Agent Systems [57.450132281381066]
  Backdoor behavior can be activated when peer evidence reaches a hidden threshold, rather than being determined by any single message.<n>We introduce a collective evidence-threshold backdoor paradigm for MAS and Boundary-Conditioned Backdoor Injection (BCBI)<n>We propose LAtent Transition Test-time Evaluation (LATTE), a clean-only latent-transition defense that learns benign communication dynamics and quarantines anomalous agent updates.
  arXiv  Detail & Related papers  (2026-08-02T08:38:44Z)
• Governed Caste Reassignment in Heterogeneous Swarms: An Asymmetric-Trust Protocol with Audited Operator Countersignature [7.392721604463545]
  We argue that for regulated embodied deployments a caste change elevates a robot's privilege envelope is a governance event that must be auditable and externally authorised.<n>We propose an asymmetric-trust protocol: auto-tightening reassignments are admitted automatically, while bounded relaxation requires an operator countersignature.<n>We evaluate a reference implementation with real Ed25519 signatures over fleets up to 100 robots.
  arXiv  Detail & Related papers  (2026-07-06T03:34:07Z)
• What to Test Next: Interpretable Coverage Gap Discovery in Driving VLMs [52.50210189669399]
  Driving vision-language models (VLMs) must accurately understand scenes across diverse conditions defined by Operational Design Domains (ODDs)<n>We propose SliceScorer, a deterministic scoring rule for missing-slice recommendation.<n>We show that SliceNav surfaces high-risk coverage gaps more effectively than prior slice-discovery methods.
  arXiv  Detail & Related papers  (2026-06-01T03:18:01Z)
• Auditing Privacy in Multi-Tenant RAG under Account Collusion [1.253312107729806]
  Multi-tenant retrieval-augmented generation services advertise per-account differential privacy as the operative leakage boundary.<n>We identify same-index multi-account collusion as a privacy-boundary failure.<n>We design the first audit protocol that operates against unmodified RAG deployments.
  arXiv  Detail & Related papers  (2026-05-19T13:41:59Z)
• When to Think, When to Speak: Learning Disclosure Policies for LLM Reasoning [60.714416943748866]
  In single-stream autoregressive interfaces, the same tokens both update the model state and constitute an irreversible public commitment.<n>We introduce Side-by-Side (SxS) Interleaved Reasoning, which makes disclosure timing a controllable decision within standard autoregressive generation.
  arXiv  Detail & Related papers  (2026-05-05T02:59:58Z)
• TwinGate: Stateful Defense against Decompositional Jailbreaks in Untraceable Traffic via Asymmetric Contrastive Learning [60.68349524623048]
  Decompositional jailbreaks pose a critical threat to large language models.<n>We present TwinGate, a stateful dual-encoder defense framework.<n>We construct a comprehensive dataset of over 3.62 million instructions spanning 8,600 distinct malicious intents.
  arXiv  Detail & Related papers  (2026-04-30T13:44:01Z)
• GoAT-X: A Graph of Auditing Thoughts for Securing Token Transactions in Cross-Chain Contracts [52.51342355102833]
  Cross-chain bridges, the critical infrastructure of the multi-chain ecosystem, have become a primary target for attackers.<n>Existing defenses, such as bytecode-level static analysis, are ill-equipped to handle the semantic complexity of cross-chain interactions.<n>We propose GoAT-X, a framework that shifts automated cross-chain smart contracts auditing from pattern matching toward systematic first-principles verification.
  arXiv  Detail & Related papers  (2026-04-27T11:34:21Z)
• Committed SAE-Feature Traces for Audited-Session Substitution Detection in Hosted LLMs [2.6382975801439836]
  Hosted-LLM providers have a silent-substitution incentive: advertise a stronger model while serving cheaper replies.<n>We propose a commit-open protocol that closes this gap.<n>We instantiate the protocol on three backbones -- Qwen3-1.7B, Gemma-2-2B, and a 4.5x scale-up to Gemma-2-9B with a 131k-feature SAE.
  arXiv  Detail & Related papers  (2026-04-20T12:34:56Z)
• MEV-ACE: Identity-Authenticated Fair Ordering for Proposer-Controlled MEV Mitigation [1.7429038786735553]
  Maximal Extractable Value, or MEV, remains a structural threat to blockchain fairness.<n>This paper presents MEV ACE, a fair ordering protocol for proposer controlled ordering MEV.<n>The protocol remains single slot in structure, requires no threshold decryption committee, and is compatible with post quantum signature schemes such as ML DSA 44.
  arXiv  Detail & Related papers  (2026-04-08T20:12:06Z)
• Pipeline Parallelism is All You Need for Optimized Early-Exit Based Self-Speculative Decoding [73.67253077506672]
  Large language models (LLMs) deliver impressive generation quality, but incur very high inference cost.<n>Early-exit based self-speculative decoding (EESD) has emerged to mitigate this cost.<n>We propose Pipeline-Parallel Self-Speculative Decoding (PPSD) that fully pipelines the draft and verification work.
  arXiv  Detail & Related papers  (2025-09-19T04:51:41Z)
• PROF: Protected Order Flow in a Profit-Seeking World [8.76739307907209]
  This work introduces a system called PROF that is designed to limit harmful forms of maximal-extractable value (MEV) in existing PBS systems. PROF imposes an ordering on a set ("bundle") of privately input transactions and enforces that ordering all the way through to block production. We quantitatively and qualitatively analyze incentive structure of PROF, and its utility to users compared with existing solutions.
  arXiv  Detail & Related papers  (2024-08-05T08:26:10Z)
• Blockchain Large Language Models [65.7726590159576]
  This paper presents a dynamic, real-time approach to detecting anomalous blockchain transactions. The proposed tool, BlockGPT, generates tracing representations of blockchain activity and trains from scratch a large language model to act as a real-time Intrusion Detection System.
  arXiv  Detail & Related papers  (2023-04-25T11:56:18Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.