collaborators

9 papers

cs.DC2026

HearthNet: Edge Multi-Agent Orchestration for Smart Homes

Zhonghao Zhan, Krinos Li, Yefan Zhang +1

Smart-home users increasingly want to control their homes in natural language rather than assemble rules, dashboards, and API integrations by hand. At the same time, real deploymen…

cs.CR2026

Systems-Level Attack Surface of Edge Agent Deployments on IoT

Zhonghao Zhan, Krinos Li, Yefan Zhang +1

Edge deployment of LLM agents on IoT hardware introduces attack surfaces absent from cloud-hosted orchestration. We present an empirical security analysis of three architectures (c…

cs.DC2026

Poster: EdgeCitadel -- Hybrid NATS-MQTT Orchestration for Edge Multi-Agent Systems

Zhonghao Zhan, Yefan Zhang, Hamed Haddadi

Edge-resident AI agents increasingly span home servers, IoT hubs, laptops, and phones, yet their coordination stacks still assume cloud-style transports or a central relay. We pres…

cs.AI2026

How Adversarial Environments Mislead Agentic AI?

Zhonghao Zhan, Huichi Zhou, Zhenhao Li +3

Tool-integrated agents are deployed on the premise that external tools ground their outputs in reality. Yet this very reliance creates a critical attack surface. Current evaluation…

cs.CR2025

AegisMCP: Online Graph Intrusion Detection for Tool-Augmented LLMs on Edge Devices

Zhonghao Zhan, Amir Al Sadi, Krinos Li +1

In this work, we study security of Model Context Protocol (MCP) agent toolchains and their applications in smart homes. We introduce AegisMCP, a protocol-level intrusion detector.…

cs.CL2025

Large Language Models Meet Virtual Cell: A Survey

Krinos Li, Xianglu Xiao, Shenglong Deng +7

Large language models (LLMs) are transforming cellular biology by enabling the development of "virtual cells"--computational systems that represent, predict, and reason about cellu…