Genetic Algorithm-Based Dynamic Backdoor Attack on Federated Learning-Based Network Traffic Classification

no code implementations • 27 Sep 2023 • Mahmoud Nazzal, Nura Aljaafari, Ahmed Sawalmeh, Abdallah Khreishah, Muhammad Anan, Abdulelah Algosaibi, Mohammed Alnaeem, Adel Aldalbahi, Abdulaziz Alhumam, Conrado P. Vizcarra, Shadan Alhamed

In this paper, we propose GABAttack, a novel genetic algorithm-based backdoor attack against federated learning for network traffic classification.

Backdoor Attack Federated Learning +1

Adversarial Attacks and Defenses for Social Network Text Processing Applications: Techniques, Challenges and Future Research Directions

no code implementations • 26 Oct 2021 • Izzat Alsmadi, Kashif Ahmad, Mahmoud Nazzal, Firoj Alam, Ala Al-Fuqaha, Abdallah Khreishah, Abdulelah Algosaibi

These vulnerabilities allow adversaries to launch a diversified set of adversarial attacks on these algorithms in different applications of social media text processing.

Hate Speech Detection Misinformation +1

ManiGen: A Manifold Aided Black-box Generator of Adversarial Examples

no code implementations • 11 Jul 2020 • Guanxiong Liu, Issa Khalil, Abdallah Khreishah, Abdulelah Algosaibi, Adel Aldalbahi, Mohammed Alaneem, Abdulaziz Alhumam, Mohammed Anan

Through extensive set of experiments on different datasets, we show that (1) adversarial examples generated by ManiGen can mislead standalone classifiers by being as successful as the state-of-the-art white-box generator, Carlini, and (2) adversarial examples generated by ManiGen can more effectively attack classifiers with state-of-the-art defenses.