SS-ZKR is a novel, three-mechanism protocol that enables privacy-preserving, content-based semantic routing of agent payloads across organizational trust boundaries without requiring the intermediary…

The paper introduces the Agent Name Service (ANS), a DNS-inspired trust layer implemented in Kubernetes, to provide secure discovery, identity, and governance for autonomous AI agents.

The paper proposes a Semantic Gateway and a Zero-Trust security model to formally validate and secure autonomous AI agents operating in enterprise systems, achieving a 100% discovery rate of unauthori…

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 introduces a comprehensive security framework, AgentRFC, to systematically analyze and test the security conformance of various AI agent protocols, identifying critical design gaps, especial…

Pepper is a novel, high-bandwidth anonymous broadcast protocol that achieves cryptographic sender anonymity and significantly improves messaging throughput compared to existing state-of-the-art system…

The paper develops a unified, cross-layer security framework for autonomous LLM agents operating in agentic commerce, identifying key attack vectors and proposing a layered defense architecture.

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…

The paper introduces Heartbeat-Bound Hierarchical Credentials (HBHC), a cryptographic protocol that revokes AI agent credentials locally and deterministically when the parent agent loses liveness, sig…

zkSBOM introduces a zero-knowledge mechanism for sharing Software Bills of Materials (SBOMs) that allows consumers to check for vulnerabilities without suppliers revealing the full, sensitive contents…

The paper proposes the Secret-Use Delegation Protocol (SUDP) to solve the Agent Secret Use (ASU) problem, ensuring that autonomous agents can perform user-authorized operations without gaining reusabl…

The paper proposes Proof-Carrying Agent Actions (PCAA), a runtime-neutral governance model that uses action certificates to consistently track and authorize high-risk actions across diverse and hetero…

The paper introduces AIP, a novel protocol using Invocation-Bound Capability Tokens (IBCTs) to provide verifiable identity and secure delegation across Model Context Protocol (MCP) and Agent-to-Agent…

The paper proposes Hermes Seal, a zk-SNARK framework that enables autonomous vehicles to generate cryptographic proofs of their internal computations and perceptions without revealing sensitive propri…

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 addresses the vulnerability of zero-knowledge proximity proofs in stateful systems by proposing Zairn-ZKP, a method that embeds operational context (like drop identity and policy version) di…

The paper introduces Distributed Sentinel, a zero-trust architecture that prevents Context-Fragmented Violations (CFVs) in multi-agent systems by propagating security state across departmental boundar…

The paper introduces MAGIQ, a novel, quantum-resistant framework designed to securely define and enforce communication and access-control policies within multi-agent AI systems.

The paper introduces Semantic Intent Fragmentation (SIF), an attack class demonstrating that multi-agent AI orchestrators can violate security policies through a composition of individually benign sub…

The paper proposes Sello, a novel protocol that allows an owner to reconstruct a tamper-evident and verifiable record of AI agent actions by having a trusted receiver sign and publish receipts of the…