Cryptographic certificates of validity for trustworthy AI
- URL: http://arxiv.org/abs/2606.23768v1
- Date: Mon, 22 Jun 2026 16:42:25 GMT
- Title: Cryptographic certificates of validity for trustworthy AI
- Abstract summary: We propose cryptographic certificates of validity for agentic AI systems.<n>An agent's action can be accompanied by an independently checkable proof that it satisfies an agreed formal policy.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: We propose cryptographic certificates of validity for agentic AI systems. The core idea is to formally specify a correctness or policy condition as a logical predicate, compile this predicate to a witness-checking problem over polynomial constraints, and use a succinct cryptographic proof system (and optionally zero-knowledge) to certify that the condition holds. This offers a middle ground between formal verification of source code, and cryptographic authentication. An agent's action can be accompanied by an independently checkable proof that it satisfies an agreed formal policy, without requiring the verifier to trust the agent or to re-execute computation. We outline the approach at a high level, give the core mathematical translation, relate the proposal to proof-carrying code, zkVMs, formal methods, and agent governance, and note the specification, auditing, and deployment questions that a full implementation must answer.
Related papers
- ProofPulse: Interactive Proof Coverage Analysis for Dafny [47.23158426199152]
Deductive verification ensures that an implementation satisfies its specification, but successful verification does not guarantee the quality of the specification.<n>We present proofpulse, a tool for Dafny that diagnoses specification quality using a three-valued proof coverage model.
arXiv Detail & Related papers (2026-08-31T14:00:31Z) - Zero-Knowledge Predicate Proofs Between AI Agents: A Measured, Cross-Protocol Gateway and the Source-Integrity Gap [0.0]
Multi-agent AI platforms move quickly from staging to production, but the way agents establish trust remains rudimentary.<n>We take provable data minimisation between agents from proposal to running system.<n>A 32-bit threshold predicate proves in 6.2 ms and verifies in 1.0 ms with a 608-byte Bulletproofs proof.
arXiv Detail & Related papers (2026-08-30T23:16:17Z) - AI Slop and Hallucinations in Vulnerability Assessment: A Survey on Reasoning Failures and Trustworthy Mitigation [48.55515767840701]
"AI slop" is artifacts, hallucinated vulnerabilities, plausible but incorrect patches, and semantically repackaged bug reports.<n>This paper surveys the empirical evidence, identifies a unifying mechanism, and traces a path toward trustworthy triage.
arXiv Detail & Related papers (2026-08-26T11:48:38Z) - Toward cryptographically verifiable authorization for autonomous AI agents: A security hypothesis, preliminary formal model, and proof-of-concept implementation [0.0]
This paper hypothesizes that agent authorization can be formalized as a cryptographically verifiable relation.<n>We introduce a preliminary formal abstraction for Cryptographically Verifiable Agent Authorization (CVA)
arXiv Detail & Related papers (2026-07-23T13:55:02Z) - Citation-Closure Retrieval and Per-Rule Attribution for Real-World Regulatory Compliance Question Answering [54.97384993676565]
We formalize Regulatory Compliance QA with RegOps-Bench, a novel benchmark featuring an Operational Knowledge Graph derived from complex national R&D regulations.<n>RefWalk traverses cross-document citations, fuses multi-view candidates via max-based aggregation, and enforces per-rule attribution to explicitly map claims to sources.
arXiv Detail & Related papers (2026-05-28T10:38:38Z) - Zero-Knowledge Model Checking [8.04509170587377]
We introduce a technology to formally verify that a software system satisfies a temporal specification of functional correctness, without revealing the system itself.<n>Our method combines a deductive approach to model checking to obtain a formal certificate of correctness for the system, with zero-knowledge proofs to convince an external verifier that the system -- kept secret -- complies with its specification of correctness -- made public.
arXiv Detail & Related papers (2026-05-01T07:53:51Z) - Compliance-by-Construction Argument Graphs: Using Generative AI to Produce Evidence-Linked Formal Arguments for Certification-Grade Accountability [0.0]
This paper proposes a compliance-by-construction architecture that integrates Generative AI (GenAI) with structured formal argument representations.<n>The architecture treats each AI-assisted step as a claim that must be supported by verifiable evidence and validated against explicit reasoning constraints.<n>The analysis suggests that validation rules can prevent unsupported claims from entering the decision record while allowing GenAI to accelerate argument construction.
arXiv Detail & Related papers (2026-04-05T12:55:16Z) - Preventing the Collapse of Peer Review Requires Verification-First AI [49.995126139461085]
We propose truth-coupling, i.e. how tightly venue scores track latent scientific truth.<n>We formalize two forces that drive a phase transition toward proxy-sovereign evaluation.
arXiv Detail & Related papers (2026-01-23T17:17:32Z) - Binding Agent ID: Unleashing the Power of AI Agents with accountability and credibility [46.323590135279126]
BAID (Binding Agent ID) is a comprehensive identity infrastructure establishing verifiable user-code binding.<n>We implement and evaluate a complete prototype system, demonstrating the practical feasibility of blockchain-based identity management and zkVM-based authentication protocol.
arXiv Detail & Related papers (2025-12-19T13:01:54Z) - Typed Chain-of-Thought: A Curry-Howard Framework for Verifying LLM Reasoning [0.0]
Chain-of-Thought (CoT) prompting enhances the reasoning capabilities of large language models.<n>We propose a novel theoretical lens for this problem grounded in the Curry-Howard correspondence.<n>We operationalise this analogy, presenting methods to extract and map the informal, natural language steps of CoT into a formal, typed proof structure.
arXiv Detail & Related papers (2025-10-01T16:06:40Z) - VeriLLM: A Lightweight Framework for Publicly Verifiable Decentralized Inference [3.8760740008451156]
We introduce VeriLLM, a publicly verifiable protocol for decentralized language models (LLMs) inference.<n>VeriLLM combines lightweight empirical rerunning with cryptographic commitments, allowing verifiers to validate results at approximately 1% of the underlying inference cost.<n>We show that VeriLLM achieves reliable public verifiability with minimal overhead.
arXiv Detail & Related papers (2025-09-29T04:07:32Z) - VulAgent: Hypothesis-Validation based Multi-Agent Vulnerability Detection [55.957275374847484]
VulAgent is a multi-agent vulnerability detection framework based on hypothesis validation.<n>It implements a semantics-sensitive, multi-view detection pipeline, each aligned to a specific analysis perspective.<n>On average, VulAgent improves overall accuracy by 6.6%, increases the correct identification rate of vulnerable--fixed code pairs by up to 450%, and reduces the false positive rate by about 36%.
arXiv Detail & Related papers (2025-09-15T02:25:38Z) - Safe and Certifiable AI Systems: Concepts, Challenges, and Lessons Learned [45.44933002008943]
This white paper presents the T"UV AUSTRIA Trusted AI framework.<n>It is an end-to-end audit catalog and methodology for assessing and certifying machine learning systems.<n>Building on three pillars - Secure Software Development, Functional Requirements, and Ethics & Data Privacy - it translates the high-level obligations of the EU AI Act into specific, testable criteria.
arXiv Detail & Related papers (2025-09-08T17:52:08Z) - Quantum Proofs of Deletion for Learning with Errors [91.3755431537592]
We construct the first fully homomorphic encryption scheme with certified deletion.
Our main technical ingredient is an interactive protocol by which a quantum prover can convince a classical verifier that a sample from the Learning with Errors distribution in the form of a quantum state was deleted.
arXiv Detail & Related papers (2022-03-03T10:07:32Z) - Interrogating the Black Box: Transparency through Information-Seeking
Dialogues [9.281671380673306]
We propose to construct an investigator agent to query a learning agent to investigate its adherence to an ethical policy.
This formal dialogue framework is the main contribution of this paper.
We argue that the introduced formal dialogue framework opens many avenues both in the area of compliance checking and in the analysis of properties of opaque systems.
arXiv Detail & Related papers (2021-02-09T09:14:04Z)
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.