most citedEnterprise-Grade Security for the Model Context Protocol (MCP): Frameworks and Mitigation Strategies

2 citations · 6 across the 6 of their papers we have counts for

collaborators

8 papers

cs.AI2025

Agent Capability Negotiation and Binding Protocol (ACNBP)

Ken Huang, Akram Sheriff, Vineeth Sai Narajala +1

As multi-agent systems evolve to encompass increasingly diverse and specialized agents, the challenge of enabling effective collaboration between heterogeneous agents has become pa…

cs.AI2025

COALESCE: Economic and Security Dynamics of Skill-Based Task Outsourcing Among Team of Autonomous LLM Agents

Manish Bhatt, Ronald F. Del Rosario, Vineeth Sai Narajala +1

The meteoric rise and proliferation of autonomous Large Language Model (LLM) agents promise significant capabilities across various domains. However, their deployment is increasing…

cs.CR20251 cited

ETDI: Mitigating Tool Squatting and Rug Pull Attacks in Model Context Protocol (MCP) by using OAuth-Enhanced Tool Definitions and Policy-Based Access Control

Manish Bhatt, Vineeth Sai Narajala, Idan Habler

The Model Context Protocol (MCP) plays a crucial role in extending the capabilities of Large Language Models (LLMs) by enabling integration with external tools and data sources. Ho…

cs.CR20252 cited

A Novel Zero-Trust Identity Framework for Agentic AI: Decentralized Authentication and Fine-Grained Access Control

Ken Huang, Vineeth Sai Narajala, John Yeoh +6

Traditional Identity and Access Management (IAM) systems, primarily designed for human users or static machine identities via protocols such as OAuth, OpenID Connect (OIDC), and SA…

cs.CR20251 cited

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

Ken Huang, Vineeth Sai Narajala, Idan Habler +1

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…

cs.CR2025

Securing Agentic AI: A Comprehensive Threat Model and Mitigation Framework for Generative AI Agents

Vineeth Sai Narajala, Om Narayan

As generative AI (GenAI) agents become more common in enterprise settings, they introduce security challenges that differ significantly from those posed by traditional systems. The…