173 citations · 185 across the 6 of their papers we have counts for
7 papers · 1 filter
PhishSSL: Self-Supervised Contrastive Learning for Phishing Website Detection
Wenhao Li, Selvakumar Manickam, Yung-Wey Chong +3
Phishing websites remain a persistent cybersecurity threat by mimicking legitimate sites to steal sensitive user information. Existing machine learning-based detection methods ofte…
PhishDebate: An LLM-Based Multi-Agent Framework for Phishing Website Detection
Wenhao Li, Selvakumar Manickam, Yung-wey Chong +1
Phishing websites remain a major cybersecurity threat, exploiting deceptive structures, brand impersonation, and social engineering to evade detection. Recent advances in large lan…
The End of the Canonical IoT Botnet: A Measurement Study of Mirai's Descendants
Leon Böck, Valentin Sundermann, Isabella Fusari +3
Since the burgeoning days of IoT, Mirai has been established as the canonical IoT botnet. Not long after the public release of its code, researchers found many Mirai variants compe…
Federated Learning Attacks Revisited: A Critical Discussion of Gaps, Assumptions, and Evaluation Setups
Aidmar Wainakh, Ephraim Zimmer, Sandeep Subedi +5
Federated learning (FL) enables a set of entities to collaboratively train a machine learning model without sharing their sensitive data, thus, mitigating some privacy concerns. Ho…
Malware Sight-Seeing: Accelerating Reverse-Engineering via Point-of-Interest-Beacons
August See, Maximilian Gehring, Max Mühlhäuser +2
New types of malware are emerging at concerning rates. However, analyzing malware via reverse engineering is still a time-consuming and mostly manual task. For this reason, it is n…
I Trust my Zombies: A Trust-enabled Botnet
Emmanouil Vasilomanolakis, Jan Helge Wolf, Leon Böck +2
Defending against botnets has always been a cat and mouse game. Cyber-security researchers and government agencies attempt to detect and take down botnets by playing the role of th…