Fabio Pierazzi

发表

Dos and Don'ts of Machine Learning in Computer Security

K. Rieck, Dan Arp, Erwin Quiring, 2020, USENIX Security Symposium.

TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time

Lorenzo Cavallaro, Fabio Pierazzi, Johannes Kinder, 2018, USENIX Security Symposium.

Enabling Fair ML Evaluations for Security

Feargus Pendlebury, Fabio Pierazzi, L. Cavallaro, 2018, CCS.

A Probabilistic Logic of Cyber Deception

Sushil Jajodia, V. S. Subrahmanian, Gerardo I. Simari, 2017, IEEE Transactions on Information Forensics and Security.

Scalable Architecture for Multi-User Encrypted SQL Operations on Cloud Database Services

Michele Colajanni, Luca Ferretti, Mirco Marchetti, 2014, IEEE Transactions on Cloud Computing.

Analysis of high volumes of network traffic for Advanced Persistent Threat detection

Michele Colajanni, Mirco Marchetti, Fabio Pierazzi, 2016, Comput. Networks.

Exploratory security analytics for anomaly detection

Michele Colajanni, Mirco Marchetti, Sara Casolari, 2016, Comput. Secur..

INSOMNIA: Towards Concept-Drift Robustness in Network Intrusion Detection

Feargus Pendlebury, Fabio Pierazzi, L. Cavallaro, 2021, AISec@CCS.

Countering Advanced Persistent Threats through security intelligence and big data analytics

Michele Colajanni, Mirco Marchetti, Fabio Pierazzi, 2016, 2016 8th International Conference on Cyber Conflict (CyCon).

Are Machine Learning Models for Malware Detection Ready for Prime Time?

Feargus Pendlebury, Fabio Pierazzi, L. Cavallaro, 2023, IEEE Security & Privacy.

Transcending TRANSCEND: Revisiting Malware Classification in the Presence of Concept Drift

Feargus Pendlebury, Fabio Pierazzi, L. Cavallaro, 2020, 2022 IEEE Symposium on Security and Privacy (SP).

Investigating Labelless Drift Adaptation for Malware Detection

Feargus Pendlebury, Fabio Pierazzi, L. Cavallaro, 2021, AISec@CCS.

Transcending Transcend: Revisiting Malware Classification with Conformal Evaluation pdf

Lorenzo Cavallaro, Fabio Pierazzi, Federico Barbero, 2020, ArXiv.

Intriguing Properties of Adversarial ML Attacks in the Problem Space

Feargus Pendlebury, Fabio Pierazzi, L. Cavallaro, 2019, 2020 IEEE Symposium on Security and Privacy (SP).

Universal Adversarial Perturbations for Malware pdf

Gabi Dreo Rodosek, Lorenzo Cavallaro, Luis Munoz-Gonz'alez, 2021, ArXiv.

“Real Attackers Don't Compute Gradients”: Bridging the Gap Between Adversarial ML Research and Practice

Kevin A. Roundy, Fabio Pierazzi, H. Anderson, 2022, 2023 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML).

A Data-driven Characterization of Modern Android Spyware

V. S. Subrahmanian, Michele Colajanni, Ghita Mezzour, 2020, ACM Trans. Manag. Inf. Syst..

Detection and Threat Prioritization of Pivoting Attacks in Large Networks

Michele Colajanni, Fabio Pierazzi, Mirco Marchetti, 2020, IEEE Transactions on Emerging Topics in Computing.

EC2: Ensemble Clustering and Classification for Predicting Android Malware Families

V. S. Subrahmanian, Tanmoy Chakraborty, Fabio Pierazzi, 2020, IEEE Transactions on Dependable and Secure Computing.

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: Predictive Behavioral Analysis of Recent Android Banking Troj

Qian Han, V. S. Subrahmanian, Ghita Mezzour, 2021, IEEE Transactions on Dependable and Secure Computing.

Enabling Fair ML Evaluations for Security

Lorenzo Cavallaro, Fabio Pierazzi, Johannes Kinder, 2018, CCS.

Is It Overkill? Analyzing Feature-Space Concept Drift in Malware Detectors

Feargus Pendlebury, Fabio Pierazzi, L. Cavallaro, 2023, 2023 IEEE Security and Privacy Workshops (SPW).

Realizable Universal Adversarial Perturbations for Malware

Gabi Dreo Rodosek, Feargus Pendlebury, Fabio Pierazzi, 2021, 2102.06747.

Performance and Cost Evaluation of an Adaptive Encryption Architecture for Cloud Databases

Michele Colajanni, Luca Ferretti, Mirco Marchetti, 2014, IEEE Transactions on Cloud Computing.

Scalable architecture for online prioritisation of cyber threats

Michele Colajanni, Mirco Marchetti, Fabio Pierazzi, 2017, 2017 9th International Conference on Cyber Conflict (CyCon).

The Network Perspective of Cloud Security

Mirco Marchetti, Fabio Pierazzi, Alessandro Guido, 2015, 2015 IEEE Fourth Symposium on Network Cloud Computing and Applications (NCCA).

Glyph: Efficient ML-Based Detection of Heap Spraying Attacks

Michele Colajanni, Mirco Marchetti, Fabio Pierazzi, 2021, IEEE Transactions on Information Forensics and Security.

Jigsaw Puzzle: Selective Backdoor Attack to Subvert Malware Classifiers

Feargus Pendlebury, Fabio Pierazzi, L. Cavallaro, 2022, 2023 IEEE Symposium on Security and Privacy (SP).

Lessons Learned on Machine Learning for Computer Security

Dan Arp, Erwin Quiring, Feargus Pendlebury, 2023, IEEE Security & Privacy.

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: Predictive Behavioral Analysis of Recent Android Banking Troj

V. S. Subrahmanian, Fabio Pierazzi, Chongyang Bai, 2019, IEEE Transactions on Dependable and Secure Computing.

Drift Forensics of Malware Classifiers

Fabio Pierazzi, Lorenz Linhardt, Zeliang Kan, 2023, AISec@CCS.

Poster: RPAL-Recovering Malware Classifiers from Data Poisoning using Active Learning

Fabio Pierazzi, Zeliang Kan, Lorenzo Cavallaro, 2023, CCS.

Unraveling the Key of Machine Learning Solutions for Android Malware Detection

Fabio Pierazzi, Jiahao Liu, Jun Zeng, 2024, 2402.02953.

This paper is included in the Proceedings of the 31st USENIX Security Symposium.

Feargus Pendlebury, Fabio Pierazzi, Christian Wressnegger, 2022 .

How to Train your Antivirus: RL-based Hardening through the Problem-Space

Fabio Pierazzi, B. Bosanský, Ilias Tsingenopoulos, 2024, ArXiv.

TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time (Extended Version)

Feargus Pendlebury, Fabio Pierazzi, Roberto Jordaney, 2024, ArXiv.

Transcending TRANSCEND: Revisiting Malware Classification in the Presence of Concept Drift

Feargus Pendlebury, Fabio Pierazzi, L. Cavallaro, 2020, 2022 IEEE Symposium on Security and Privacy (SP).

Intriguing Properties of Adversarial ML Attacks in the Problem Space

Lorenzo Cavallaro, Fabio Pierazzi, Jacopo Cortellazzi, 2019, 2020 IEEE Symposium on Security and Privacy (SP).

Intriguing Properties of Adversarial ML Attacks in the Problem Space [Extended Version]

Erwin Quiring, Feargus Pendlebury, Fabio Pierazzi, 2019, 1911.02142.