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ORCIDLorenzo Cavallaro
- > Home > Persons > Lorenzo Cavallaro
Publications
- 2025
[j13]Jacopo Cortellazzi
, Erwin Quiring, Daniel Arp, Feargus Pendlebury, Fabio Pierazzi, Lorenzo Cavallaro:
Intriguing Properties of Adversarial ML Attacks in the Problem Space [Extended Version]. ACM Trans. Priv. Secur. 28(4): 42:1-42:37 (2025)- [c63]Ilias Tsingenopoulos, Vera Rimmer, Davy Preuveneers, Fabio Pierazzi, Lorenzo Cavallaro, Wouter Joosen:
The Adaptive Arms Race: Redefining Robustness in AI Security. RAID 2025: 611-628 - [c62]Yigitcan Kaya, Yizheng Chen, Marcus Botacin, Shoumik Saha, Fabio Pierazzi, Lorenzo Cavallaro, David A. Wagner, Tudor Dumitras:
ML-Based Behavioral Malware Detection Is Far From a Solved Problem. SaTML 2025: 921-940 - [i29]Theo Chow, Mario D'Onghia, Lorenz Linhardt, Zeliang Kan, Daniel Arp, Lorenzo Cavallaro, Fabio Pierazzi:
Breaking Out from the TESSERACT: Reassessing ML-based Malware Detection under Spatio-Temporal Drift. CoRR abs/2506.23814 (2025) - 2024
- [j12]Daniel Arp, Erwin Quiring, Feargus Pendlebury, Alexander Warnecke, Fabio Pierazzi, Christian Wressnegger, Lorenzo Cavallaro, Konrad Rieck:
Pitfalls in Machine Learning for Computer Security. Commun. ACM 67(11): 104-112 (2024) - [c59]Shae McFadden, Zeliang Kan, Lorenzo Cavallaro, Fabio Pierazzi:
The Impact of Active Learning on Availability Data Poisoning for Android Malware Classifiers. ACSAC Workshops 2024: 73-84 - [c58]Davide Rusconi, Matteo Zoia, Luca Buccioli, Fabio Pierazzi, Danilo Bruschi, Lorenzo Cavallaro, Flavio Toffalini, Andrea Lanzi:
EmbedWatch: Fat Pointer Solution for Detecting Spatial Memory Errors in Embedded Systems. CPSIOTSEC@CCS 2024: 55-67 - [c55]Ilias Tsingenopoulos, Jacopo Cortellazzi, Branislav Bosanský, Simone Aonzo, Davy Preuveneers, Wouter Joosen, Fabio Pierazzi, Lorenzo Cavallaro:
How to Train your Antivirus: RL-based Hardening through the Problem Space. RAID 2024: 130-146 - [i26]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 abs/2402.01359 (2024) - [i25]Jiahao Liu, Jun Zeng, Fabio Pierazzi, Lorenzo Cavallaro, Zhenkai Liang:
Unraveling the Key of Machine Learning Solutions for Android Malware Detection. CoRR abs/2402.02953 (2024) - [i24]Jacopo Cortellazzi, Ilias Tsingenopoulos, Branislav Bosanský, Simone Aonzo, Davy Preuveneers, Wouter Joosen, Fabio Pierazzi, Lorenzo Cavallaro:
How to Train your Antivirus: RL-based Hardening through the Problem-Space. CoRR abs/2402.19027 (2024) - [i23]Yigitcan Kaya, Yizheng Chen, Shoumik Saha, Fabio Pierazzi, Lorenzo Cavallaro, David A. Wagner, Tudor Dumitras:
Demystifying Behavior-Based Malware Detection at Endpoints. CoRR abs/2405.06124 (2024) - [i20]Hamid Bostani, Jacopo Cortellazzi, Daniel Arp, Fabio Pierazzi, Veelasha Moonsamy, Lorenzo Cavallaro:
On the Effectiveness of Adversarial Training on Malware Classifiers. CoRR abs/2412.18218 (2024) - 2023
- [j10]Lorenzo Cavallaro, Johannes Kinder, Feargus Pendlebury, Fabio Pierazzi:
Are Machine Learning Models for Malware Detection Ready for Prime Time? IEEE Secur. Priv. 21(2): 53-56 (2023) - [j9]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): 72-77 (2023) - [c53]Theo Chow, Zeliang Kan, Lorenz Linhardt, Lorenzo Cavallaro, Daniel Arp, Fabio Pierazzi:
Drift Forensics of Malware Classifiers. AISec@CCS 2023: 197-207 - [c52]Shae McFadden, Zeliang Kan, Lorenzo Cavallaro, Fabio Pierazzi:
Poster: RPAL-Recovering Malware Classifiers from Data Poisoning using Active Learning. CCS 2023: 3561-3563 - [c47]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: 21-28 - [c46]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: 719-736 - [i15]Ilias Tsingenopoulos, Vera Rimmer, Davy Preuveneers, Fabio Pierazzi, Lorenzo Cavallaro, Wouter Joosen:
Adversarial Markov Games: On Adaptive Decision-Based Attacks and Defenses. CoRR abs/2312.13435 (2023) - 2022
- [c44]Federico Barbero, Feargus Pendlebury, Fabio Pierazzi, Lorenzo Cavallaro:
Transcending TRANSCEND: Revisiting Malware Classification in the Presence of Concept Drift. SP 2022: 805-823 - [c43]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: 3971-3988 - [i14]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 abs/2202.05470 (2022) - 2021
- [c42]Giuseppina Andresini, Feargus Pendlebury, Fabio Pierazzi, Corrado Loglisci, Annalisa Appice, Lorenzo Cavallaro:
INSOMNIA: Towards Concept-Drift Robustness in Network Intrusion Detection. AISec@CCS 2021: 111-122 - [c41]Zeliang Kan, Feargus Pendlebury, Fabio Pierazzi, Lorenzo Cavallaro:
Investigating Labelless Drift Adaptation for Malware Detection. AISec@CCS 2021: 123-134 - [i11]Raphael Labaca Castro, Luis Muñoz-González, Feargus Pendlebury, Gabi Dreo Rodosek, Fabio Pierazzi, Lorenzo Cavallaro:
Universal Adversarial Perturbations for Malware. CoRR abs/2102.06747 (2021) - 2020
- [c39]Fabio Pierazzi, Feargus Pendlebury, Jacopo Cortellazzi, Lorenzo Cavallaro:
Intriguing Properties of Adversarial ML Attacks in the Problem Space. SP 2020: 1332-1349 - [i10]Federico Barbero, Feargus Pendlebury, Fabio Pierazzi, Lorenzo Cavallaro:
Transcending Transcend: Revisiting Malware Classification with Conformal Evaluation. CoRR abs/2010.03856 (2020) - [i9]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 abs/2010.09470 (2020) - 2019
- [c37]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: 729-746 - [i7]Fabio Pierazzi, Feargus Pendlebury, Jacopo Cortellazzi, Lorenzo Cavallaro:
Intriguing Properties of Adversarial ML Attacks in the Problem Space. CoRR abs/1911.02142 (2019) - 2018
- [c36]Feargus Pendlebury, Fabio Pierazzi, Roberto Jordaney, Johannes Kinder, Lorenzo Cavallaro:
Enabling Fair ML Evaluations for Security. CCS 2018: 2264-2266 - [i5]Feargus Pendlebury, Fabio Pierazzi, Roberto Jordaney, Johannes Kinder, Lorenzo Cavallaro:
TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time. CoRR abs/1807.07838 (2018)
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