Abstract is missing.
- Differentially Private Logistic Regression with Sparse SolutionsAmol Khanna, Fred Lu, Edward Raff, Brian Testa. 1-9 [doi]
- Equivariant Differentially Private Deep Learning: Why DP-SGD Needs Sparser ModelsFlorian A. Hölzl, Daniel Rueckert, Georgios Kaissis. 11-22 [doi]
- Probing the Transition to Dataset-Level Privacy in ML Models Using an Output-Specific and Data-Resolved Privacy ProfileTyler LeBlond, Joseph Munoz, Fred Lu, Maya Fuchs, Elliott Zaresky-Williams, Edward Raff, Brian Testa. 23-33 [doi]
- Information Leakage from Data Updates in Machine Learning ModelsTian Hui, Farhad Farokhi, Olga Ohrimenko. 35-41 [doi]
- Membership Inference Attacks Against Semantic Segmentation ModelsTomás Chobola, Dmitrii Usynin, Georgios Kaissis. 43-53 [doi]
- Utility-preserving Federated LearningReza Nasirigerdeh, Daniel Rueckert, Georgios Kaissis. 55-65 [doi]
- Certifiers Make Neural Networks Vulnerable to Availability AttacksTobias Lorenz 0002, Marta Kwiatkowska, Mario Fritz. 67-78 [doi]
- Not What You've Signed Up For: Compromising Real-World LLM-Integrated Applications with Indirect Prompt InjectionSahar Abdelnabi, Kai Greshake, Shailesh Mishra, Christoph Endres, Thorsten Holz, Mario Fritz. 79-90 [doi]
- Canaries and Whistles: Resilient Drone Communication Networks with (or without) Deep Reinforcement LearningChris Hicks, Vasilios Mavroudis, Myles Foley, Thomas Davies, Kate Highnam, Tim Watson. 91-101 [doi]
- The Adversarial Implications of Variable-Time InferenceDudi Biton, Aditi Misra, Efrat Levy, Jaidip Kotak, Ron Bitton, Roei Schuster, Nicolas Papernot, Yuval Elovici, Ben Nassi. 103-114 [doi]
- Dictionary Attack on IMU-based Gait AuthenticationRajesh Kumar, Can Isik, Chilukuri Krishna Mohan. 115-126 [doi]
- When Side-Channel Attacks Break the Black-Box Property of Embedded Artificial IntelligenceBenoît Coqueret, Mathieu Carbone, Olivier Sentieys, Gabriel Zaid. 127-138 [doi]
- Task-Agnostic Safety for Reinforcement LearningMd Asifur Rahman, Sarra Alqahtani. 139-148 [doi]
- Broken Promises: Measuring Confounding Effects in Learning-based Vulnerability DiscoveryErik Imgrund, Tom Ganz, Martin Härterich, Lukas Pirch, Niklas Risse, Konrad Rieck. 149-160 [doi]
- Measuring Equality in Machine Learning Security Defenses: A Case Study in Speech RecognitionLuke E. Richards, Edward Raff, Cynthia Matuszek. 161-171 [doi]
- Certified Robustness of Static Deep Learning-based Malware Detectors against Patch and Append AttacksDaniel Gibert, Giulio Zizzo, Quan Le. 173-184 [doi]
- AVScan2Vec: Feature Learning on Antivirus Scan Data for Production-Scale Malware CorporaRobert J. Joyce, Tirth Patel, Charles Nicholas, Edward Raff. 185-196 [doi]
- Drift Forensics of Malware ClassifiersTheo Chow, Zeliang Kan, Lorenz Linhardt, Lorenzo Cavallaro, Daniel Arp, Fabio Pierazzi. 197-207 [doi]
- Lookin' Out My Backdoor! Investigating Backdooring Attacks Against DL-driven Malware DetectorsMario D'Onghia, Federico Di Cesare, Luigi Gallo, Michele Carminati, Mario Polino, Stefano Zanero. 209-220 [doi]
- Reward Shaping for Happier Autonomous Cyber Security AgentsElizabeth Bates, Vasilios Mavroudis, Chris Hicks. 221-232 [doi]
- Raze to the Ground: Query-Efficient Adversarial HTML Attacks on Machine-Learning Phishing Webpage DetectorsBiagio Montaruli, Luca Demetrio, Maura Pintor, Luca Compagna, Davide Balzarotti, Battista Biggio. 233-244 [doi]