Fabio Pierazzi
King's College
H-index: 19
North America-United States
Top articles of Fabio Pierazzi
Wendigo: Deep Reinforcement Learning for Denial-of-Service Query Discovery in GraphQL
2024/3/5
Vasilios Mavroudis
H-Index: 4
Fabio Pierazzi
H-Index: 11
How to Train your Antivirus: RL-based Hardening through the Problem-Space
arXiv preprint arXiv:2402.19027
2024/2/29
Unraveling the Key of Machine Learning Solutions for Android Malware Detection
arXiv preprint arXiv:2402.02953
2024/2/5
Jiahao Liu
H-Index: 2
Jun Zeng
H-Index: 0
Fabio Pierazzi
H-Index: 11
Lorenzo Cavallaro
H-Index: 23
Zhenkai Liang
H-Index: 24
TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time (Extended Version)
arXiv preprint arXiv:2402.01359
2024/2/2
Characterizing physical adversarial attacks on robot motion planners
2024/1/29
Is it overkill? analyzing feature-space concept drift in malware detectors
2023/5/25
Are Machine Learning Models for Malware Detection Ready for Prime Time?
IEEE Security & Privacy
2023/4/14
Lorenzo Cavallaro
H-Index: 23
Johannes Kinder
H-Index: 18
Feargus Pendlebury
H-Index: 3
Fabio Pierazzi
H-Index: 11
“Real Attackers Don't Compute Gradients”: Bridging the Gap between Adversarial ML Research and Practice
2023/2/8
Jigsaw puzzle: Selective backdoor attack to subvert malware classifiers
2023/5/21
Adversarial Markov Games: On Adaptive Decision-Based Attacks and Defenses
arXiv preprint arXiv:2312.13435
2023/12/20
Drift Forensics of Malware Classifiers
2023/11/30
Zeliang Kan
H-Index: 1
Lorenz Linhardt
H-Index: 4
Lorenzo Cavallaro
H-Index: 23
Daniel Arp
H-Index: 14
Fabio Pierazzi
H-Index: 11
Poster: RPAL-Recovering Malware Classifiers from Data Poisoning using Active Learning
2023/11/15
Lessons Learned on Machine Learning for Computer Security
IEEE Security & Privacy
2023/9/6
Exploring the security and privacy risks of chatbots in messaging services
2022/10/25
WoRMA'22: 1st Workshop on Robust Malware Analysis
2022/5/30
Fabio Pierazzi
H-Index: 11
Transcending Transcend: Revisiting malware classification in the presence of concept drift
2022/5/10
Dos and don’ts of machine learning in computer security
2022
Investigating labelless drift adaptation for malware detection
2021/11/15
Zeliang Kan
H-Index: 1
Feargus Pendlebury
H-Index: 3
Fabio Pierazzi
H-Index: 11
Lorenzo Cavallaro
H-Index: 23
Insomnia: Towards concept-drift robustness in network intrusion detection
2021/11/15
Realizable universal adversarial perturbations for malware
arXiv preprint arXiv:2102.06747
2021/2/12
Luis Muñoz-González
H-Index: 11
Feargus Pendlebury
H-Index: 3
Fabio Pierazzi
H-Index: 11
Lorenzo Cavallaro
H-Index: 23
Co-Authors
