Agent Capability Negotiation and Binding Protocol (ACNBP)

As multi-agent systems evolve to encompass increasingly diverse and specialized agents, the challenge of enabling effective collaboration between heterogeneous agents has become paramount, with traditional agent communication protocols often assuming homogeneous environments or predefined interaction patterns that limit their applicability in dynamic, open-world scenarios. This paper presents the Agent Capability Negotiation and Binding Protocol (ACNBP), a novel framework designed to facilitate secure, efficient, and verifiable interactions between agents in heterogeneous multi-agent systems through integration with an Agent Name Service (ANS) infrastructure that provides comprehensive discovery, negotiation, and binding mechanisms. The protocol introduces a structured 10-step process encompassing capability discovery, candidate pre-screening and selection, secure negotiation phases, and binding commitment with built-in security measures including digital signatures, capability attestation, and comprehensive threat mitigation strategies, while a key innovation of ACNBP is its protocolExtension mechanism that enables backward-compatible protocol evolution and supports diverse agent architectures while maintaining security and interoperability. We demonstrate ACNBP's effectiveness through a comprehensive security analysis using the MAESTRO threat modeling framework, practical implementation considerations, and a detailed example showcasing the protocol's application in a document translation scenario, with the protocol addressing critical challenges in agent autonomy, capability verification, secure communication, and scalable agent ecosystem management.

ADA: Automated Moving Target Defense for AI Workloads via Ephemeral Infrastructure-Native Rotation in Kubernetes

This paper introduces the Adaptive Defense Agent (ADA), an innovative Automated Moving Target Defense (AMTD) system designed to fundamentally enhance the security posture of AI workloads. ADA operates by continuously and automatically rotating these workloads at the infrastructure level, leveraging the inherent ephemerality of Kubernetes pods. This constant managed churn systematically invalidates attacker assumptions and disrupts potential kill chains by regularly destroying and respawning AI service instances. This methodology, applying principles of chaos engineering as a continuous, proactive defense, offers a paradigm shift from traditional static defenses that rely on complex and expensive confidential or trusted computing solutions to secure the underlying compute platforms, while at the same time agnostically supporting the latest advancements in agentic and nonagentic AI ecosystems and solutions such as agent-to-agent (A2A) communication frameworks or model context protocols (MCP). This AI-native infrastructure design, relying on the widely proliferated cloud-native Kubernetes technologies, facilitates easier deployment, simplifies maintenance through an inherent zero trust posture achieved by rotation, and promotes faster adoption. We posit that ADA's novel approach to AMTD provides a more robust, agile, and operationally efficient zero-trust model for AI services, achieving security through proactive environmental manipulation rather than reactive patching.

Agent Name Service (ANS): A Universal Directory for Secure AI Agent Discovery and Interoperability

The proliferation of AI agents requires robust mechanisms for secure discovery. This paper introduces the Agent Name Service (ANS), a novel architecture based on DNS addressing the lack of a public agent discovery framework. ANS provides a protocol-agnostic registry infrastructure that leverages Public Key Infrastructure (PKI) certificates for verifiable agent identity and trust. The architecture features several key innovations: a formalized agent registration and renewal mechanism for lifecycle management; DNS-inspired naming conventions with capability-aware resolution; a modular Protocol Adapter Layer supporting diverse communication standards (A2A, MCP, ACP etc.); and precisely defined algorithms for secure resolution. We implement structured communication using JSON Schema and conduct a comprehensive threat analysis of our proposal. The result is a foundational directory service addressing the core challenges of secured discovery and interaction in multi-agent systems, paving the way for future interoperable, trustworthy, and scalable agent ecosystems.