Security and privacy of location-based services for in-vehicle device systems. - Marcello Missiroli; Fabio Pierazzi; Michele Colajanni (HPCS, 2014)

Efficient detection of unauthorized data modification in cloud databases. - Luca Ferretti; Fabio Pierazzi; Michele Colajanni; Mirco Marchetti; Marcello Missiroli (ISCC, 2014)

Performance and Cost Evaluation of an Adaptive Encryption Architecture for Cloud Databases. - Luca Ferretti; Fabio Pierazzi; Michele Colajanni; Mirco Marchetti (IEEE Trans. Cloud Comput., 2014)

Scalable Architecture for Multi-User Encrypted SQL Operations on Cloud Database Services. - Luca Ferretti; Fabio Pierazzi; Michele Colajanni; Mirco Marchetti (IEEE Trans. Cloud Comput., 2014)

The Network Perspective of Cloud Security. - Fabio Pierazzi; Andrea Balboni; Alessandro Guido; Mirco Marchetti (NCCA, 2015)

Countering Advanced Persistent Threats through security intelligence and big data analytics. - Mirco Marchetti; Fabio Pierazzi; Alessandro Guido; Michele Colajanni (CyCon, 2016)

Analysis of high volumes of network traffic for Advanced Persistent Threat detection. - Mirco Marchetti; Fabio Pierazzi; Michele Colajanni; Alessandro Guido (Comput. Networks, 2016)

Exploratory security analytics for anomaly detection. - Fabio Pierazzi; Sara Casolari; Michele Colajanni; Mirco Marchetti (Comput. Secur., 2016)

Scalable architecture for online prioritisation of cyber threats. - Fabio Pierazzi; Giovanni Apruzzese; Michele Colajanni; Alessandro Guido; Mirco Marchetti (CyCon, 2017)

A Probabilistic Logic of Cyber Deception. - Sushil Jajodia; Noseong Park; Fabio Pierazzi; Andrea Pugliese 001; Edoardo Serra; Gerardo I. Simari; V. S. Subrahmanian (IEEE Trans. Inf. Forensics Secur., 2017)

Enabling Fair ML Evaluations for Security. - Feargus Pendlebury; Fabio Pierazzi; Roberto Jordaney; Johannes Kinder; Lorenzo Cavallaro (CCS, 2018)

TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time. - Feargus Pendlebury; Fabio Pierazzi; Roberto Jordaney; Johannes Kinder; Lorenzo Cavallaro (USENIX Security Symposium, 2019)

Intriguing Properties of Adversarial ML Attacks in the Problem Space. - Fabio Pierazzi; Feargus Pendlebury; Jacopo Cortellazzi; Lorenzo Cavallaro (SP, 2020)

Transcending Transcend: Revisiting Malware Classification with Conformal Evaluation. - Federico Barbero; Feargus Pendlebury; Fabio Pierazzi; Lorenzo Cavallaro (CoRR, 2020)

EC2: Ensemble Clustering and Classification for Predicting Android Malware Families. - Tanmoy Chakraborty 002; Fabio Pierazzi; V. S. Subrahmanian (IEEE Trans. Dependable Secur. Comput., 2020)

Detection and Threat Prioritization of Pivoting Attacks in Large Networks. - Giovanni Apruzzese; Fabio Pierazzi; Michele Colajanni; Mirco Marchetti (IEEE Trans. Emerg. Top. Comput., 2020)

A Data-driven Characterization of Modern Android Spyware. - Fabio Pierazzi; Ghita Mezzour; Qian Han; Michele Colajanni; V. S. Subrahmanian (ACM Trans. Manag. Inf. Syst., 2020)

INSOMNIA: Towards Concept-Drift Robustness in Network Intrusion Detection. - Giuseppina Andresini; Feargus Pendlebury; Fabio Pierazzi; Corrado Loglisci; Annalisa Appice; Lorenzo Cavallaro (AISec@CCS, 2021)

Investigating Labelless Drift Adaptation for Malware Detection. - Zeliang Kan; Feargus Pendlebury; Fabio Pierazzi; Lorenzo Cavallaro (AISec@CCS, 2021)

Universal Adversarial Perturbations for Malware. - Raphael Labaca Castro; Luis Muñoz-González; Feargus Pendlebury; Gabi Dreo Rodosek; Fabio Pierazzi; Lorenzo Cavallaro (CoRR, 2021)

$ sf {DBank}$DBank: Predictive Behavioral Analysis of Recent Android Banking Trojans. - Chongyang Bai; Qian Han; Ghita Mezzour; Fabio Pierazzi; V. S. Subrahmanian (IEEE Trans. Dependable Secur. Comput., 2021)

Glyph: Efficient ML-Based Detection of Heap Spraying Attacks. - Fabio Pierazzi; Stefano Cristalli; Danilo Bruschi; Michele Colajanni; Mirco Marchetti; Andrea Lanzi (IEEE Trans. Inf. Forensics Secur., 2021)

WoRMA '22: 1st Workshop on Robust Malware Analysis. - Fabio Pierazzi; Nedim Srndic (AsiaCCS, 2022)

Exploring the security and privacy risks of chatbots in messaging services. - Jide S. Edu; Cliona Mulligan; Fabio Pierazzi; Jason Polakis; Guillermo Suarez-Tangil; Jose M. Such (IMC, 2022)

Transcending TRANSCEND: Revisiting Malware Classification in the Presence of Concept Drift. - Federico Barbero; Feargus Pendlebury; Fabio Pierazzi; Lorenzo Cavallaro (SP, 2022)

Dos and Don'ts of Machine Learning in Computer Security. - Daniel Arp; Erwin Quiring; Feargus Pendlebury; Alexander Warnecke; Fabio Pierazzi; Christian Wressnegger; Lorenzo Cavallaro; Konrad Rieck (USENIX Security Symposium, 2022)

Drift Forensics of Malware Classifiers. - Theo Chow; Zeliang Kan; Lorenz Linhardt; Lorenzo Cavallaro; Daniel Arp; Fabio Pierazzi (AISec@CCS, 2023)

Poster: RPAL-Recovering Malware Classifiers from Data Poisoning using Active Learning. - Shae McFadden; Zeliang Kan; Lorenzo Cavallaro; Fabio Pierazzi (CCS, 2023)

"Real Attackers Don't Compute Gradients": Bridging the Gap Between Adversarial ML Research and Practice. - Giovanni Apruzzese; Hyrum S. Anderson; Savino Dambra; David Freeman; Fabio Pierazzi; Kevin A. Roundy (SaTML, 2023)

Is It Overkill? Analyzing Feature-Space Concept Drift in Malware Detectors. - Zhi Chen 028; Zhenning Zhang; Zeliang Kan; Limin Yang; Jacopo Cortellazzi; Feargus Pendlebury; Fabio Pierazzi; Lorenzo Cavallaro; Gang Wang 011 (SP (Workshops), 2023)

Jigsaw Puzzle: Selective Backdoor Attack to Subvert Malware Classifiers. - Limin Yang; Zhi Chen 028; Jacopo Cortellazzi; Feargus Pendlebury; Kevin Tu; Fabio Pierazzi; Lorenzo Cavallaro; Gang Wang 011 (SP, 2023)

Adversarial Markov Games: On Adaptive Decision-Based Attacks and Defenses. - Ilias Tsingenopoulos; Vera Rimmer; Davy Preuveneers; Fabio Pierazzi; Lorenzo Cavallaro; Wouter Joosen (CoRR, 2023)

Lessons Learned on Machine Learning for Computer Security. - Daniel Arp; Erwin Quiring; Feargus Pendlebury; Alexander Warnecke; Fabio Pierazzi; Christian Wressnegger; Lorenzo Cavallaro; Konrad Rieck (IEEE Secur. Priv., 2023)

Are Machine Learning Models for Malware Detection Ready for Prime Time? - Lorenzo Cavallaro; Johannes Kinder; Feargus Pendlebury; Fabio Pierazzi (IEEE Secur. Priv., 2023)

The Impact of Active Learning on Availability Data Poisoning for Android Malware Classifiers. - Shae McFadden; Zeliang Kan; Lorenzo Cavallaro; Fabio Pierazzi (ACSAC Workshops, 2024)

When Adversarial Perturbations meet Concept Drift: An Exploratory Analysis on ML-NIDS. - Giovanni Apruzzese; Aurore Fass; Fabio Pierazzi (AISec@CCS, 2024)

EmbedWatch: Fat Pointer Solution for Detecting Spatial Memory Errors in Embedded Systems. - Davide Rusconi; Matteo Zoia; Luca Buccioli; Fabio Pierazzi; Danilo Bruschi; Lorenzo Cavallaro; Flavio Toffalini; Andrea Lanzi (CPSIOTSEC@CCS, 2024)

Characterizing Physical Adversarial Attacks on Robot Motion Planners. - Wenxi Wu; Fabio Pierazzi; Yali Du 001; Martim Brandão (ICRA, 2024)

How to Train your Antivirus: RL-based Hardening through the Problem Space. - Ilias Tsingenopoulos; Jacopo Cortellazzi; Branislav Bosanský; Simone Aonzo; Davy Preuveneers; Wouter Joosen; Fabio Pierazzi; Lorenzo Cavallaro (RAID, 2024)

WENDIGO: Deep Reinforcement Learning for Denial-of-Service Query Discovery in GraphQL. - Shae McFadden; Marcello Maugeri; Chris Hicks; Vasilios Mavroudis; Fabio Pierazzi (SP (Workshops), 2024)

TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time (Extended Version). - Zeliang Kan; Shae McFadden; Daniel Arp; Feargus Pendlebury; Roberto Jordaney; Johannes Kinder; Fabio Pierazzi; Lorenzo Cavallaro (CoRR, 2024)

Unraveling the Key of Machine Learning Solutions for Android Malware Detection. - Jiahao Liu; Jun Zeng 006; Fabio Pierazzi; Lorenzo Cavallaro; Zhenkai Liang (CoRR, 2024)

Demystifying Behavior-Based Malware Detection at Endpoints. - Yigitcan Kaya; Yizheng Chen 001; Shoumik Saha; Fabio Pierazzi; Lorenzo Cavallaro; David A. Wagner 001; Tudor Dumitras (CoRR, 2024)

On the Effectiveness of Adversarial Training on Malware Classifiers. - Hamid Bostani; Jacopo Cortellazzi; Daniel Arp; Fabio Pierazzi; Veelasha Moonsamy; Lorenzo Cavallaro (CoRR, 2024)

Pitfalls in Machine Learning for Computer Security. - Daniel Arp; Erwin Quiring; Feargus Pendlebury; Alexander Warnecke; Fabio Pierazzi; Christian Wressnegger; Lorenzo Cavallaro; Konrad Rieck (Commun. ACM, 2024)

ML-Based Behavioral Malware Detection Is Far From a Solved Problem. - Yigitcan Kaya; Yizheng Chen 001; Marcus Botacin; Shoumik Saha; Fabio Pierazzi; Lorenzo Cavallaro; David A. Wagner 001; Tudor Dumitras (SaTML, 2025)

Unveiling ECC Vulnerabilities: LSTM Networks for Operation Recognition in Side-Channel Attacks. - Alberto Battistello; Guido Bertoni; Michele Corrias; Lorenzo Nava; Davide Rusconi; Matteo Zoia; Fabio Pierazzi; Andrea Lanzi (CoRR, 2025)

KnowML: Improving Generalization of ML-NIDS with Attack Knowledge Graphs. - Xin Fan Guo; Albert Meroño-Peñuela; Sergio Maffeis; Fabio Pierazzi (CoRR, 2025)

Breaking Out from the TESSERACT: Reassessing ML-based Malware Detection under Spatio-Temporal Drift. - Theo Chow; Mario D'Onghia; Lorenz Linhardt; Zeliang Kan; Daniel Arp; Lorenzo Cavallaro; Fabio Pierazzi (CoRR, 2025)