Feargus Pendlebury

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 18

Top Topics

Machine Learning

Malware Detection

Data Stream Classification

Top Venues

IEEE Symposium on Security and Privacy

USENIX Security Symposium

Publications

Zeliang Kan, Shae McFadden, Daniel Arp, Feargus Pendlebury, Roberto Jordaney, Johannes Kinder, Fabio Pierazzi, Lorenzo Cavallaro
TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time (Extended Version). CoRR (2024)
Limin Yang, Zhi Chen, Jacopo Cortellazzi, Feargus Pendlebury, Kevin Tu, Fabio Pierazzi, Lorenzo Cavallaro, Gang Wang
Jigsaw Puzzle: Selective Backdoor Attack to Subvert Malware Classifiers. SP (2023)
Daniel Arp, Erwin Quiring, Feargus Pendlebury, Alexander Warnecke, Fabio Pierazzi, Christian Wressnegger, Lorenzo Cavallaro, Konrad Rieck
Lessons Learned on Machine Learning for Computer Security. IEEE Secur. Priv. 21 (5) (2023)
Lorenzo Cavallaro, Johannes Kinder, Feargus Pendlebury, Fabio Pierazzi
Are Machine Learning Models for Malware Detection Ready for Prime Time? IEEE Secur. Priv. 21 (2) (2023)
Zhi Chen, Zhenning Zhang, Zeliang Kan, Limin Yang, Jacopo Cortellazzi, Feargus Pendlebury, Fabio Pierazzi, Lorenzo Cavallaro, Gang Wang
Is It Overkill? Analyzing Feature-Space Concept Drift in Malware Detectors. SP Workshops (2023)
Limin Yang, Zhi Chen, Jacopo Cortellazzi, Feargus Pendlebury, Kevin Tu, Fabio Pierazzi, Lorenzo Cavallaro, Gang Wang
Jigsaw Puzzle: Selective Backdoor Attack to Subvert Malware Classifiers. CoRR (2022)
Federico Barbero, Feargus Pendlebury, Fabio Pierazzi, Lorenzo Cavallaro
Transcending TRANSCEND: Revisiting Malware Classification in the Presence of Concept Drift. IEEE Symposium on Security and Privacy (2022)
Daniel Arp, Erwin Quiring, Feargus Pendlebury, Alexander Warnecke, Fabio Pierazzi, Christian Wressnegger, Lorenzo Cavallaro, Konrad Rieck
Dos and Don'ts of Machine Learning in Computer Security. USENIX Security Symposium (2022)
Zeliang Kan, Feargus Pendlebury, Fabio Pierazzi, Lorenzo Cavallaro
Investigating Labelless Drift Adaptation for Malware Detection. AISec@CCS (2021)
Giuseppina Andresini, Feargus Pendlebury, Fabio Pierazzi, Corrado Loglisci, Annalisa Appice, Lorenzo Cavallaro
INSOMNIA: Towards Concept-Drift Robustness in Network Intrusion Detection. AISec@CCS (2021)
Raphael Labaca Castro, Luis Muñoz-González, Feargus Pendlebury, Gabi Dreo Rodosek, Fabio Pierazzi, Lorenzo Cavallaro
Universal Adversarial Perturbations for Malware. CoRR (2021)
Fabio Pierazzi, Feargus Pendlebury, Jacopo Cortellazzi, Lorenzo Cavallaro
Intriguing Properties of Adversarial ML Attacks in the Problem Space. IEEE Symposium on Security and Privacy (2020)
Daniel Arp, Erwin Quiring, Feargus Pendlebury, Alexander Warnecke, Fabio Pierazzi, Christian Wressnegger, Lorenzo Cavallaro, Konrad Rieck
Dos and Don'ts of Machine Learning in Computer Security. CoRR (2020)
Federico Barbero, Feargus Pendlebury, Fabio Pierazzi, Lorenzo Cavallaro
Transcending Transcend: Revisiting Malware Classification with Conformal Evaluation. CoRR (2020)
Feargus Pendlebury, Fabio Pierazzi, Roberto Jordaney, Johannes Kinder, Lorenzo Cavallaro
TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time. USENIX Security Symposium (2019)
Fabio Pierazzi, Feargus Pendlebury, Jacopo Cortellazzi, Lorenzo Cavallaro
Intriguing Properties of Adversarial ML Attacks in the Problem Space. CoRR (2019)
Feargus Pendlebury, Fabio Pierazzi, Roberto Jordaney, Johannes Kinder, Lorenzo Cavallaro
TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time. CoRR (2018)
Feargus Pendlebury, Fabio Pierazzi, Roberto Jordaney, Johannes Kinder, Lorenzo Cavallaro
Enabling Fair ML Evaluations for Security. CCS (2018)