Author

Ji He

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Preprint Aug 2026

IriSig-Spoof: A Real-World Benchmark for Time-Robust Satellite RF Fingerprinting and Spoofing Detection

Low Earth orbit (LEO) satellite Internet is becoming critical communications infrastructure, yet its open wireless links remain vulnerable to satellite impersonation and signal spoofing. Radio frequency fingerprinting (RFF) offers a potential defense by exploiting transmitter-specific hardware imperfections manifested...

Shichang Guo, Yuan-Yu Zhang, Shuang-Rui Zhao et al. · 0 citations

Preprint Sep 2026

Know the Normal, Track the Attack: Context-Grounded and Stateful LLM Investigation over System Provenance

Provenance-based intrusion detection systems (PIDSs) identify suspicious activity in audit streams, but their outputs remain difficult to turn into coherent attack narratives. Direct LLM analyses of local anomalous subgraphs lack deployment-specific normal-behavior knowledge and validated attack state across evidence f...

Li-Jie Zheng, Ji He, Ying Wang et al. · 0 citations

Preprint Sep 2026

One Pipeline Does Not Fit All: TAILOR, a Type- and State-Aware Framework for CVE Reproduction

TAILOR broadens the coverage of automated CVE reproduction and provides auditable evidence for vulnerability diagnosis and defense and ablation experiments show that the two control levels respectively mitigate execution-path mismatch and missing Web prerequisite state.

Ji He, Huang Zhang, Li-Jie Zheng et al. · 0 citations

Review Open access 2026

A Multi-Agent DevSecOps Framework for Intelligent Vulnerability Detection and Auto-Remediation

This paper presents a multi-agent DevSecOps framework that integrates static code scanning, large language model (LLM) based security reasoning, automated repair generation, policy-as-code enforcement, and runtime monitoring into a unified event-driven pipeline. Five specialized agents collaborate through LangGraph sha...

Hai-Ning Fan, Li-Jie Zheng, Chen-Hao Han et al. · Journal of networking and ne... · 0 citations

#machine learning Preprint Sep 2026

Not All Relations Are Equal: Relation-Balanced and Calibrated Graph Learning for Provenance-Based Intrusion Detection

RECAL is presented, an unsupervised framework using relation-balanced masked graph learning to better capture rare interaction patterns and calibrates reconstruction errors against each relation's benign error distribution to produce comparable anomaly evidence, helping distinguish attacks from benign behavior and redu...

Li-Jie Zheng, Ji He, Zhi-Wei Zhang et al. · 0 citations