AmBox is a system that integrates ambient sensors directly with a blockchain to provide secure, verifiable, and tamper-resistant data for enhanced food traceability throughout the supply chain.

The paper proposes a tamper-proof fraud detection system that uses blockchain smart contracts to immutably record ML predictions and workflow executions, addressing the vulnerability of controllable a…

The paper proposes a trustless framework using dual-layer cryptographic commitments to solve the operator-gating problem in blockchain provenance trees, ensuring verifiable user attribution even when…

The paper proposes a lightweight, Merkle-tree-based pipeline for verifying the integrity of IoT audit logs, achieving high throughput and low latency without the overhead of blockchain technology.

This paper advances the lightweight blockchain verification protocol, FlyClient, by addressing technical challenges, introducing a new adversary model, and providing practical implementations and opti…

The paper proposes Agentic Witnessing, a TEE-enabled framework that allows external verifiers to audit the qualitative properties of private datasets by querying an LLM-based auditor without accessing…

This paper analyzes the technical challenges of auditing novel cryptoassets and custody mechanisms by employing an autoethnographic framework derived from the author's multi-role professional experien…

Aegon is a new protocol that provides an auditable, tamper-evident infrastructure for tracking AI content licensing transactions and compliance receipts.

The paper proposes a blockchain-based, governance-constrained agentic AI architecture for wildfire monitoring that enforces mandatory human oversight to ensure safety, reliability, and accountability…

This paper synthesizes the emerging field of blockchain and AI for securing intelligent networks by providing a comprehensive taxonomy, integration patterns, and an evaluation blueprint.

The paper proposes a decentralized, witnessing-zone architecture that enhances Proof-of-Location (PoL) to provide robust, auditable evidence of physical events, thereby improving sensor data trustwort…

QCIVET introduces a novel contract-based framework to ensure the integrity of hybrid quantum-classical pipelines by verifying both the structure (syntactic) and the behavior (semantic) of quantum stag…

This paper proposes and evaluates the integration of Federated Learning and blockchain technology over cloud-edge infrastructure to enhance data privacy and security for decentralized AI applications.

LiteAtt introduces a verifier-less, Peer-to-Peer Self-Attestation (P2P-SA) framework for modern IoT MCUs, enabling mutual authentication and firmware attestation directly within the connection handsha…

The paper proposes an attestation-aware promotion gate to mitigate supply-chain risks in LLM pipelines by cryptographically verifying and enforcing claims about training and release artifacts before d…

HadAgent introduces a decentralized AI serving system that replaces resource-intensive Proof-of-Work with Proof-of-Inference (PoI) to secure LLM agent operations and achieve fast, verifiable consensus…

The paper proposes an evidence-driven protocol combining Deterministic Build Systems and Trusted Execution Environments to provide cryptographically verifiable guarantees of software artifact integrit…

This paper proposes a decentralized, blockchain-based protocol using both public and private blockchains to enhance the cyber resilience and security of IoT data transfer for digital building twins an…

GoAT-X introduces a novel framework that structures cross-chain smart contract auditing as a Graph of Auditing Thoughts, significantly improving the detection of complex, semantic vulnerabilities in m…

The paper introduces KindHML, an automated formal verification approach that uses Hennessy-Milner Logic and the Kind 2 model checker to verify complex temporal properties of smart contracts, detecting…