Provable Mutual Benefits from Federated Learning in Privacy-Sensitive Domains
Authors: Nikita Tsoy, Anna Mihalkova, Teodora Todorova, Nikola Konstantinov | Published: 2024-03-11 | Updated: 2024-11-07
Poisoning
Fake or Compromised? Making Sense of Malicious Clients in Federated Learning
Authors: Hamid Mozaffari, Sunav Choudhary, Amir Houmansadr | Published: 2024-03-10
Enhancing Security in Federated Learning through Adaptive Consensus-Based Model Update Validation
Authors: Zahir Alsulaimawi | Published: 2024-03-05
Mitigating Label Flipping Attacks in Malicious URL Detectors Using Ensemble Trees
Authors: Ehsan Nowroozi, Nada Jadalla, Samaneh Ghelichkhani, Alireza Jolfaei | Published: 2024-03-05
Federated Learning Under Attack: Exposing Vulnerabilities through Data Poisoning Attacks in Computer Networks
Authors: Ehsan Nowroozi, Imran Haider, Rahim Taheri, Mauro Conti | Published: 2024-03-05
Enhancing Data Provenance and Model Transparency in Federated Learning Systems — A Database Approach
Authors: Michael Gu, Ramasoumya Naraparaju, Dongfang Zhao | Published: 2024-03-03
Analysis of Privacy Leakage in Federated Large Language Models
Authors: Minh N. Vu, Truc Nguyen, Tre' R. Jeter, My T. Thai | Published: 2024-03-02
Defending Against Data Reconstruction Attacks in Federated Learning: An Information Theory Approach
Authors: Qi Tan, Qi Li, Yi Zhao, Zhuotao Liu, Xiaobing Guo, Ke Xu | Published: 2024-03-02
Transfer Learning for Security: Challenges and Future Directions
Authors: Adrian Shuai Li, Arun Iyengar, Ashish Kundu, Elisa Bertino | Published: 2024-03-01
Indiscriminate Data Poisoning Attacks on Pre-trained Feature Extractors
Authors: Yiwei Lu, Matthew Y. R. Yang, Gautam Kamath, Yaoliang Yu | Published: 2024-02-20