The paper argues that traditional identity-based reputation mechanisms are structurally inapplicable to language model agents because their mutable, modular nature makes them ontologically dissociativ…

This paper proposes TRM-Raft, a Byzantine-resistant enhancement for Raft consensus that integrates a Blockchain-based Trust and Reputation Model to prevent election forgery and log tampering.

The paper introduces DARTIC, a decentralized, anonymous, and scalable reputation framework that allows on-chain crowdsourcing to maintain accountability and trust while preserving user privacy.

The paper proposes IPEK, a context-aware trust mechanism for VANETs, which significantly improves detection of intelligent attackers by incorporating event and location severity into trust calculation…

This pilot study investigates SME readiness for Zero Trust Architecture (ZTA) and proposes a realistic three-stage adoption path based on survey data from IT professionals.

The paper simulates bargaining scenarios using LLM agents to analyze how optimizing agents for financial profit affects their honesty and trust, finding that while fine-tuning improves deal-making, it…

The paper introduces MolTrust, a production-deployed trust infrastructure built on W3C standards (VCs and DIDs) that provides a verifiable, multi-layered authorization framework for autonomous AI agen…

The paper proposes Proof of Useful Attestation (PoUA), a consensus mechanism that weights validator vote power not just by staked capital, but also by a reputation score earned through performing vali…

The paper proposes a dual-regime architecture combining Bernoulli CUSUM and asymmetric scoring to significantly improve trust fraud detection in sparse rating networks, achieving superior performance…

The paper proposes DySCo, a dynamic trust-aware sparse consensus mechanism, to efficiently manage communication in multi-agent LLM systems by selectively connecting agents based on real-time value, th…

This paper surveys the trustworthiness of agentic AI systems in engineering domains, organizing it around five dimensions: safety, robustness, transparency, accountability, and privacy.

The paper proposes a novel hybrid authorization framework that combines roles and First-Order Logic to enforce fine-grained, triple-level access control for autonomous agents interacting with knowledg…

KYA introduces a framework-agnostic trust and governance layer for autonomous systems that ensures actions are authorized, policy-conforming, and verifiable through a combination of novel primitives.

The paper proposes a trust schema and verification framework to ensure that agent skills, which augment LLMs, are rigorously verified before deployment, thereby making human-in-the-loop oversight scal…

The paper systematizes the interaction between autonomous AI agents and blockchain platforms using a bidirectional trust framework, identifying significant gaps in current standards and proposing a ta…

This paper proposes an empirical methodology to automate web application trustworthiness assessment by leveraging Large Language Models (LLMs) to verify adherence to secure coding practices, showing t…

This study investigates human-AI collaboration in question answering, finding that while collaboration is beneficial, humans make suboptimal decisions by both under-relying on correct AI suggestions a…

The paper proposes a methodology for auditable trustworthiness levels in AI governance with a formal framework and a lightweight procedure.