Browse by UCL people
Group by: Type | Date
Jump to: Article | Proceedings paper
Number of items: 15.
Article
Arp, Daniel;
Quiring, Erwin;
Pendlebury, Feargus;
Warnecke, Alexander;
Pierazzi, Fabio;
Wressnegger, Christian;
Cavallaro, Lorenzo;
(2024)
Pitfalls in Machine Learning for Computer Security.
Communications of the ACM
, 67
(11)
pp. 104-112.
10.1145/3643456.
|
 |
|
Bai, C;
Han, Q;
Mezzour, G;
Pierazzi, F;
Subrahmanian, VS;
(2021)
DBank: Predictive Behavioral Analysis of Recent Android Banking Trojans.
IEEE Transactions on Dependable and Secure Computing
, 18
(3)
pp. 1378-1393.
10.1109/TDSC.2019.2909902.
|
|
|
Cortellazzi, Jacopo;
Pendlebury, Feargus;
Arp, Daniel;
Quiring, Erwin;
Pierazzi, Fabio;
Cavallaro, Lorenzo;
(2025)
Intriguing Properties of Adversarial ML Attacks in the Problem Space [Extended Version].
ACM Transactions on Privacy and Security (TOPS)
TOPS-2024-04-0123.R2.
(In press).
|
|
|
Pierazzi, F;
Cristalli, S;
Bruschi, D;
Colajanni, M;
Marchetti, M;
Lanzi, A;
(2020)
Glyph: Efficient ML-Based Detection of Heap Spraying Attacks.
IEEE Transactions on Information Forensics and Security
, 16
pp. 740-755.
10.1109/TIFS.2020.3017925.
|
|
Proceedings paper
|
Apruzzese, G;
Anderson, HS;
Dambra, S;
Freeman, D;
Pierazzi, F;
Roundy, K;
(2023)
'Real Attackers Don't Compute Gradients': Bridging the Gap between Adversarial ML Research and Practice.
In:
Proceedings - 2023 IEEE Conference on Secure and Trustworthy Machine Learning, SaTML 2023.
(pp. pp. 339-364).
IEEE: Raleigh, NC, USA.
|
|
|
Apruzzese, G;
Fass, A;
Pierazzi, F;
(2024)
When Adversarial Perturbations meet Concept Drift: an Exploratory Analysis on ML-NIDS.
In:
AISec 2024 - Proceedings of the 2024 Workshop on Artificial Intelligence and Security, Co-Located with: CCS 2024.
(pp. pp. 149-160).
ACM
|
|
|
Edu, J;
Mulligan, C;
Pierazzi, F;
Polakis, J;
Suarez-Tangil, G;
Such, J;
(2022)
Exploring the Security and Privacy Risks of Chatbots in Messaging Services.
In:
Proceedings of the ACM SIGCOMM Internet Measurement Conference, IMC.
(pp. pp. 581-588).
Association for computering Machinery (ACM): Nice, Fance.
|
|
|
Kaya, Yigitcan;
Chen, Yizheng;
Botacin, Marcus;
Saha, Shoumik;
Pierazzi, Fabio;
Cavallaro, Lorenzo;
Wagner, David;
(2025)
ML-Based Behavioral Malware Detection Is Far
From a Solved Problem.
In:
Proceedings of the 3rd IEEE Conference on Secure and Trustworthy Machine Learning.
IEEE: Copenhagen, Denmark.
(In press).
|
|
|
McFadden, S;
Maugeri, M;
Hicks, C;
Mavroudis, V;
Pierazzi, F;
(2024)
WENDIGO: Deep Reinforcement Learning for Denial-of-Service Query Discovery in GraphQL.
In:
Proceedings - 45th IEEE Symposium on Security and Privacy Workshops, SPW 2024.
(pp. pp. 68-75).
IEEE: San Francisco, CA, USA.
|
 |
|
McFadden, Shae;
Kan, Zeliang;
Cavallaro, Lorenzo;
Pierazzi, Fabio;
(2025)
The Impact of Active Learning on Availability Data Poisoning for Android Malware Classifiers.
In:
2024 Annual Computer Security Applications Conference Workshops (ACSAC Workshops).
(pp. pp. 73-84).
IEEE: Honolulu, HI, USA.
|
|
|
Pendlebury, Feargus;
Pierazzi, Fabio;
Jordaney, Roberto;
Kinder, Johannes;
Cavallaro, Lorenzo;
(2019)
TESSERACT: eliminating experimental bias in malware classification across space and time.
In:
SEC'19: Proceedings of the 28th USENIX Conference on Security Symposium.
(pp. pp. 729-746).
USENIX Association: Berkeley, CAUnited States.
|
|
|
Rusconi, Davide;
Zoia, Matteo;
Buccioli, Luca;
Pierazzi, Fabio;
Bruschi, Danilo;
Cavallaro, Lorenzo;
Toffalini, Flavio;
(2024)
EmbedWatch: Fat Pointer Solution for Detecting Spatial Memory Errors in Embedded Systems.
In:
CPSIoTSec'24: Proceedings of the Sixth Workshop on CPS&IoT Security and Privacy.
(pp. pp. 55-67).
ACM: New York, NY, USA.
|
|
|
Tsingenopoulos, I;
Cortellazzi, J;
Bošanský, B;
Aonzo, S;
Preuveneers, D;
Joosen, W;
Pierazzi, F;
(2024)
How to Train your Antivirus: RL-based Hardening through the Problem Space.
In:
ACM International Conference Proceeding Series.
(pp. pp. 130-146).
Association for Computering Machinery (ACM): Padua, Italy.
|
|
Tsingenopoulos, Ilias;
Rimmer, Vera;
Preuveneers, Davy;
Pierazzi, Fabio;
Cavallaro, Lorenzo;
Joosen, Wouter;
(2025)
The Adaptive Arms Race: Redefining Robustness in AI Security.
In:
Proceedings of The 28th International Symposium on Research in Attacks, Intrusions and Defenses (RAID 2025).
Research in Attacks, Intrusions and Defenses (RAID): Gold Coast, Australia.
(In press).
|
|
|
Wu, W;
Pierazzi, F;
Du, Y;
Brandão, M;
(2024)
Characterizing Physical Adversarial Attacks on Robot Motion Planners.
In:
Proceedings - IEEE International Conference on Robotics and Automation.
(pp. pp. 14319-14325).
IEEE: Yokohama, Japan.
|
|
