Browse by UCL people
Group by: Type | Date
Number of items: 42.
2026
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Zhu, Yiran;
Tang, Tong;
Wan, Jie;
Yang, Ziqi;
Liu, Zhenguang;
Cavallaro, Lorenzo;
(2026)
BINALIGNER: Aligning Binary Code for Cross-Compilation Environment Diffing.
In:
(Proceedings) Network and Distributed System Security (NDSS) Symposium.
: San Diego, CA, USA.
(In press).
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2025
Capozzi, G;
Tang, T;
Wan, J;
Yang, Z;
D'Elia, DC;
Di Luna, GA;
Cavallaro, L;
(2025)
On the Lack of Robustness of Binary Function Similarity Systems.
In:
2025 IEEE 10th European Symposium on Security and Privacy (EuroS&P).
(pp. pp. 980-1001).
IEEE: Venice, Italy.
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Cavallaro, Lorenzo;
Saha, Aakanksha;
Mattei, James;
Blasco, Jorge;
Votipka, Daniel;
Lindorfer, Martina;
(2025)
Expert insights into advanced persistent threats: analysis, attribution, and challenges.
In:
Proceedings of the 34th USENIX Security Symposium.
USENIX: Seattle, WA, USA.
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He, Yiling;
She, Hongyu;
Qian, Xingzhi;
Zheng, Xinran;
Chen, Zhuo;
Qin, Zhan;
Cavallaro, Lorenzo;
(2025)
On Benchmarking Code LLMs for Android Malware Analysis.
In:
Proceedings of the 34th ACM SIGSOFT International Symposium on Software Testing and Analysis.
(pp. pp. 153-160).
ACM: New York, NY, USA.
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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.
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Qian, Xingzhi;
Zheng, Xinran;
He, Yiling;
Yang, Shuo;
Cavallaro, Lorenzo;
(2025)
LAMD: Context-driven Android Malware Detection and Classification with LLMs.
In: Blanton, M and Enck, W and Nita-Rotaru, C, (eds.)
2025 IEEE Security and Privacy Workshops (SPW).
(pp. pp. 126-136).
IEEE: San Francisco, CA, USA.
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2024
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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.
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De Pasquale, G;
Grishchenko, I;
Iesari, R;
Pizarro, G;
Cavallaro, L;
Kruegel, C;
Vigna, G;
(2024)
ChainReactor: Automated Privilege Escalation Chain Discovery via AI Planning.
In:
Proceedings of the 33rd USENIX Security Symposium.
(pp. pp. 5913-5929).
USENIX: Philadelphia, PA, USA.
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Gray, Jason;
Sgandurra, Daniele;
Cavallaro, Lorenzo;
Blasco Alis, Jorge;
(2024)
Identifying Authorship in Malicious Binaries: Features, Challenges & Datasets.
ACM Computing Surveys
, 56
(8)
, Article 212. 10.1145/3653973.
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Pei, Kexin;
Li, Weichen;
Jin, Qirui;
Liu, Shuyang;
Geng, Scott;
Cavallaro, Lorenzo;
Yang, Junfeng;
(2024)
Exploiting Code Symmetries for Learning Program Semantics.
In: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix, (eds.)
Proceedings of the 41st International Conference on Machine Learning.
(pp. pp. 40092-40113).
Proceedings of Machine Learning Research (PMLR): Vienna, Austria.
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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.
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Saha, Aakanksha;
Blasco, Jorge;
Cavallaro, Lorenzo;
Lindorfer, Martina;
(2024)
ADAPT it! Automating APT Campaign and Group Attribution by Leveraging and Linking Heterogeneous Files.
In:
Proceedings of RAID '24: Proceedings of the 27th International Symposium on Research in Attacks, Intrusions and Defenses.
(pp. pp. 114-129).
ACM
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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.
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2023
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Arp, Daniel;
Quiring, Erwin;
Pendlebury, Feargus;
Warnecke, Alexander;
Pierazzi, Fabio;
Wressnegger, Christian;
Cavallaro, Lorenzo;
(2023)
Lessons Learned on Machine Learning for Computer Security.
IEEE Security & Privacy
, 21
(5)
pp. 72-77.
10.1109/msec.2023.3287207.
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Cavallaro, Lorenzo;
Kinder, Johannes;
Pendlebury, Feargus;
Pierazzi, Fabio;
(2023)
Are Machine Learning Models for Malware Detection Ready for Prime Time?
IEEE Security and Privacy Magazine
, 21
(2)
pp. 53-56.
10.1109/msec.2023.3236543.
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Chen, Z;
Zhang, Z;
Kan, Z;
Yang, L;
Cortellazzi, J;
Pendlebury, F;
Pierazzi, F;
... Wang, G; + view all
(2023)
Is It Overkill? Analyzing Feature-Space Concept Drift in Malware Detectors.
In:
Proceedings of the IEEE Security and Privacy Workshops (SPW) 2023.
(pp. pp. 21-28).
Institute of Electrical and Electronics Engineers (IEEE)
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Chow, Theo;
Kan, Zeliang;
Linhardt, Lorenz;
Cavallaro, Lorenzo;
Arp, Daniel;
Pierazzi, Fabio;
(2023)
Drift Forensics of Malware Classifiers.
In:
Proceedings of the 16th ACM Workshop on Artificial Intelligence and Security.
(pp. pp. 197-207).
ACM: Copenhagen, Denmark.
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De Pasquale, Giulio;
Nakanishi, Fukutomo;
Ferla, Daniele;
Cavallaro, Lorenzo;
(2023)
ROPfuscator: Robust Obfuscation with ROP.
In:
2023 IEEE Security and Privacy Workshops (SPW).
(pp. pp. 228-237).
IEEE: San Francisco, CA, USA.
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McFadden, Shae;
Kan, Zeliang;
Cavallaro, Lorenzo;
Pierazzi, Fabio;
(2023)
Poster: RPAL-Recovering Malware Classifiers from Data Poisoning using Active Learning.
In:
Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security.
(pp. pp. 3561-3563).
ACM: Copenhagen, Denmark.
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Pan, Kun;
Yin, Yifang;
Wei, Yao;
Lin, Feng;
Ba, Zhongjie;
Liu, Zhenguang;
Wang, Zhibo;
... Ren, Kui; + view all
(2023)
DFIL: Deepfake Incremental Learning by Exploiting Domain-invariant Forgery Clues.
In:
MM '23: Proceedings of the 31st ACM International Conference on Multimedia.
(pp. pp. 8035-8046).
ACM (Association for Computing Machinery)
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Shuai, Chao;
Zhong, Jieming;
Wu, Shuang;
Lin, Feng;
Wang, Zhibo;
Ba, Zhongjie;
Liu, Zhenguang;
... Ren, Kui; + view all
(2023)
Locate and Verify: A Two-Stream Network for Improved Deepfake Detection.
In:
Proceedings of the 31st ACM International Conference on Multimedia.
(pp. pp. 7131-7142).
ACM (Association for Computing Machinery)
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Yang, L;
Chen, Z;
Cortellazzi, J;
Pendlebury, F;
Tu, K;
Pierazzi, F;
Cavallaro, L;
(2023)
Jigsaw Puzzle: Selective Backdoor Attack to Subvert Malware Classifiers.
In:
Proceedings of the IEEE Symposium on Security and Privacy (SP) 2023.
(pp. pp. 719-736).
Institute of Electrical and Electronics Engineers (IEEE)
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2022
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Arp, D;
Quiring, E;
Pendlebury, F;
Warnecke, A;
Pierazzi, F;
Wressnegger, C;
Cavallaro, L;
(2022)
Dos and Don'ts of Machine Learning in Computer Security.
In:
Proceedings of the 31st USENIX Security Symposium.
USENIX
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Barbero, Federico;
Pendlebury, Feargus;
Pierazzi, Fabio;
Cavallaro, Lorenzo;
(2022)
Transcending Transcend: Revisiting Malware Classification in the Presence of Concept Drift.
In:
2022 IEEE Symposium on Security and Privacy (SP).
IEEE: San Francisco, CA, USA.
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Chen, Ju;
Wang, Jinghan;
Song, Chengyu;
Yin, Heng;
(2022)
JIGSAW: Efficient and Scalable Path Constraints Fuzzing.
In:
Proceedings of the IEEE Symposium on Security and Privacy (SP) 2022.
(pp. pp. 18-35).
Institute of Electrical and Electronics Engineers (IEEE)
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Toffalini, Flavio;
Mathias, Payer;
Zhou, Jianying;
Cavallaro, Lorenzo;
(2022)
Designing a Provenance Analysis for SGX Enclaves.
In:
(Proceedings) Annual Computer Security Applications Conference (ACSAC).
(In press).
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2021
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Andresini, G;
Pendlebury, F;
Pierazzi, F;
Loglisci, C;
Appice, A;
Cavallaro, L;
(2021)
INSOMNIA: Towards Concept-Drift Robustness in Network Intrusion Detection.
In:
AISec '21: Proceedings of the 14th ACM Workshop on Artificial Intelligence and Security.
Association for Computing Machinery: Virtual, Republic of Korea.
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Cavallaro, L;
Gray, J;
Sgandurra, D;
(2021)
Identifying Authorship Style in Malicious Binaries: Techniques, Challenges & Datasets.
ArXiv
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Kan, Z;
Pendlebury, F;
Pierazzi, F;
Cavallaro, L;
(2021)
Investigating Labelless Drift Adaptation for Malware Detection.
In:
AISec '21: Proceedings of the 14th ACM Workshop on Artificial Intelligence and Security.
(pp. pp. 123-134).
ACM
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Labaca-Castro, R;
Muñoz-González, L;
Pendlebury, F;
Dreo Rodosek, G;
Pierazzi, F;
Cavallaro, L;
(2021)
Realizable Universal Adversarial Perturbations for Malware.
ArXiv
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2020
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D'Elia, DC;
Coppa, E;
Palmaro, F;
Cavallaro, L;
(2020)
On the Dissection of Evasive Malware.
IEEE Transactions on Information Forensics and Security
, 15
pp. 2750-2765.
10.1109/TIFS.2020.2976559.
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Nakanishi, F;
De Pasquale, G;
Ferla, D;
Cavallaro, L;
(2020)
Intertwining ROP Gadgets and Opaque Predicates for Robust Obfuscation.
arXiv
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Patrick-Evans, J;
Cavallaro, L;
Kinder, J;
(2020)
Probabilistic Naming of Functions in Stripped Binaries.
In:
ACSAC '20: Annual Computer Security Applications Conference.
(pp. pp. 373-385).
ACM
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Pierazzi, F;
Pendlebury, F;
Cortellazzi, J;
Cavallaro, L;
(2020)
Intriguing Properties of Adversarial ML Attacks in the Problem Space.
In:
2020 IEEE Symposium on Security and Privacy (SP).
IEEE: San Francisco, CA, USA.
(In press).
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2019
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D'Elia, Daniele Cono;
Coppa, Emilio;
Nicchi, Simone;
Palmaro, Federico;
Cavallaro, Lorenzo;
(2019)
SoK: Using Dynamic Binary Instrumentation for Security (And How You May Get Caught Red Handed).
In:
Proceedings of the 2019 ACM Asia conference on Computer and Communications Security (Asia CCS '19).
(pp. pp. 15-27).
ACM (Association for Computing Machinery): New York, NY, United States.
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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.
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2018
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Suarez-Tangil, G;
Dash, SK;
Garcia-Teodoro, P;
Camacho, J;
Cavallaro, L;
(2018)
Anomaly-based exploratory analysis and detection of exploits in android mediaserver.
IET Information Security
, 12
(5)
pp. 404-413.
10.1049/iet-ifs.2017.0460.
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2017
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Hurier, M;
Suarez-Tangil, G;
Dash, SK;
Bissyande, TF;
Le Traon, Y;
Klein, J;
Cavallaro, L;
(2017)
Euphony: Harmonious Unification of Cacophonous Anti-Virus Vendor Labels for Android Malware.
In:
Proceedings of the 2017 IEEE/ACM 14th International Conference on Mining Software Repositories (MSR).
(pp. pp. 425-435).
IEEE: Buenos Aires, Argentina.
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Jordaney, R;
Sharad, K;
Dash, SK;
Wang, Z;
Papini, D;
Nouretdinov, I;
Cavallaro, L;
(2017)
Transcend: Detecting Concept Drift in Malware Classification Models.
In:
Proceedings of the 26th USENIX Security Symposium.
(pp. pp. 625-642).
USENIX Association: Vancouver, Canada.
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Mba, G;
Onaolapo, J;
Stringhini, G;
Cavallaro, L;
(2017)
Flipping 419 Cybercrime Scams: Targeting the Weak and the Vulnerable.
In: Barrett, R and Cummings, R and Agichtein, E and Gabrilovich, E, (eds.)
Proceedings of the 26th International Conference on World Wide Web Companion.
(pp. pp. 1301-1310).
ACM
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Patrick-Evans, James;
Cavallaro, Lorenzo;
Kinder, Johannes;
(2017)
POTUS: probing off-the-shelf USB drivers with symbolic fault injection.
In:
WOOT'17: Proceedings of the 11th USENIX Conference on Offensive Technologies.
(pp. pp. 1-10).
USENIX Association: New York, NY, United States.
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Repel, Dusan;
Kinder, Johannes;
Cavallaro, Lorenzo;
(2017)
Modular Synthesis of Heap Exploits.
In:
PLAS '17: Proceedings of the 2017 Workshop on Programming Languages and Analysis for Security.
(pp. pp. 25-35).
ACM (Association for Computing Machinery): New York, NY, United States.
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