Protection against Source Inference Attacks in Federated Learning
Authors: Andreas Athanasiou, Kangsoo Jung, Catuscia Palamidessi | Published: 2026-03-02
ポイズニング
A Unified Evaluation of Learning-Based Similarity Techniques for Malware Detection
Authors: Udbhav Prasad, Aniesh Chawla | Published: 2026-02-17
Comparative Insights on Adversarial Machine Learning from Industry and Academia: A User-Study Approach
Authors: Vishruti Kakkad, Paul Chung, Hanan Hibshi, Maverick Woo | Published: 2026-02-04
IoT-based Android Malware Detection Using Graph Neural Network With Adversarial Defense
Authors: Rahul Yumlembam, Biju Issac, Seibu Mary Jacob, Longzhi Yang | Published: 2025-12-23
GShield: Mitigating Poisoning Attacks in Federated Learning
Authors: Sameera K. M., Serena Nicolazzo, Antonino Nocera, Vinod P., Rafidha Rehiman K. A | Published: 2025-12-22
From One Attack Domain to Another: Contrastive Transfer Learning with Siamese Networks for APT Detection
Authors: Sidahmed Benabderrahmane, Talal Rahwan | Published: 2025-11-25
Can Federated Learning Safeguard Private Data in LLM Training? Vulnerabilities, Attacks, and Defense Evaluation
Authors: Wenkai Guo, Xuefeng Liu, Haolin Wang, Jianwei Niu, Shaojie Tang, Jing Yuan | Published: 2025-09-25
Not All Samples Are Equal: Quantifying Instance-level Difficulty in Targeted Data Poisoning
Authors: William Xu, Yiwei Lu, Yihan Wang, Matthew Y. R. Yang, Zuoqiu Liu, Gautam Kamath, Yaoliang Yu | Published: 2025-09-08
On the Security and Privacy of Federated Learning: A Survey with Attacks, Defenses, Frameworks, Applications, and Future Directions
Authors: Daniel M. Jimenez-Gutierrez, Yelizaveta Falkouskaya, Jose L. Hernandez-Ramos, Aris Anagnostopoulos, Ioannis Chatzigiannakis, Andrea Vitaletti | Published: 2025-08-19
Non-omniscient backdoor injection with a single poison sample: Proving the one-poison hypothesis for linear regression and linear classification
Authors: Thorsten Peinemann, Paula Arnold, Sebastian Berndt, Thomas Eisenbarth, Esfandiar Mohammadi | Published: 2025-08-07