How many perturbations break this model? Evaluating robustness beyond adversarial accuracy
Authors: Raphael Olivier, Bhiksha Raj | Published: 2022-07-08 | Updated: 2023-08-10
Defense Method
Federated and Transfer Learning: A Survey on Adversaries and Defense Mechanisms
Authors: Ehsan Hallaji, Roozbeh Razavi-Far, Mehrdad Saif | Published: 2022-07-05
Defending against the Label-flipping Attack in Federated Learning
Authors: Najeeb Moharram Jebreel, Josep Domingo-Ferrer, David Sánchez, Alberto Blanco-Justicia | Published: 2022-07-05
Special Session: Towards an Agile Design Methodology for Efficient, Reliable, and Secure ML Systems
Authors: Shail Dave, Alberto Marchisio, Muhammad Abdullah Hanif, Amira Guesmi, Aviral Shrivastava, Ihsen Alouani, Muhammad Shafique | Published: 2022-04-18
Machine Learning Security against Data Poisoning: Are We There Yet?
Authors: Antonio Emanuele Cinà, Kathrin Grosse, Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo | Published: 2022-04-12 | Updated: 2024-03-08
Breaking the De-Pois Poisoning Defense
Authors: Alaa Anani, Mohamed Ghanem, Lotfy Abdel Khaliq | Published: 2022-04-03
Trojan Horse Training for Breaking Defenses against Backdoor Attacks in Deep Learning
Authors: Arezoo Rajabi, Bhaskar Ramasubramanian, Radha Poovendran | Published: 2022-03-25
Email Summarization to Assist Users in Phishing Identification
Authors: Amir Kashapov, Tingmin Wu, Alsharif Abuadbba, Carsten Rudolph | Published: 2022-03-24
MERLIN — Malware Evasion with Reinforcement LearnINg
Authors: Tony Quertier, Benjamin Marais, Stéphane Morucci, Bertrand Fournel | Published: 2022-03-24 | Updated: 2022-03-30
RES-HD: Resilient Intelligent Fault Diagnosis Against Adversarial Attacks Using Hyper-Dimensional Computing
Authors: Onat Gungor, Tajana Rosing, Baris Aksanli | Published: 2022-03-14