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DAVE-CC: A decentralized, access-controlled, verifiable ecosystem for cross-chain academic credential management

RESEARCH CREW
22:01 23/09/2025
TIN LIÊN QUAN
MAF-LLM: A Multi-Agent Framework Based on Large Language Models for Automated Ransomware Memory Forensics
MAF-LLM: A Multi-Agent Framework Based on Large Language Models for Automated Ransomware Memory Forensics
P4P: A Probe-Guided Anti-Poisoning Defense for Federated Learning-based Intrusion Detection in IoT Networks under Non-IID Data
Federated learning (FL) enables collaborative Intrusion Detection Systems (IDS) across distributed Internet of Things (IoT) networks without sharing raw data. However, its openness exposes it to model poisoning and backdoor attacks, where malicious clients manipulate updates to corrupt the global model. Detecting such threats remains difficult under non-independent and identically...
AutoWAFuzzer: An Adaptive Framework for Web Application Firewall Penetration Testing with Multi-agent System and RAG-enabled Reinforcement Learning
Web Application Firewalls (WAFs) are crucial in mitigating web-based threats such as SQLi and XSS, yet the evolving complexity of WAF detection mechanisms poses significant challenges for penetration testing (pentest) tools. Existing ML- and RL-based fuzzers often suffer from three main limitations: (1) reliance on static training datasets, making them...