4 citations · 20 across the 14 of their papers we have counts for
4 papers · 1 filter
DiPSeN: Differentially Private Self-normalizing Neural Networks For Adversarial Robustness in Federated Learning
Olakunle Ibitoye, M. Omair Shafiq, Ashraf Matrawy
The need for robust, secure and private machine learning is an important goal for realizing the full potential of the Internet of Things (IoT). Federated learning has proven to hel…
A GAN-based Approach for Mitigating Inference Attacks in Smart Home Environment
Olakunle Ibitoye, Ashraf Matrawy, M. Omair Shafiq
The proliferation of smart, connected, always listening devices have introduced significant privacy risks to users in a smart home environment. Beyond the notable risk of eavesdrop…
Evaluation of Adversarial Training on Different Types of Neural Networks in Deep Learning-based IDSs
Rana Abou Khamis, Ashraf Matrawy
Network security applications, including intrusion detection systems of deep neural networks, are increasing rapidly to make detection task of anomaly activities more accurate and…
Investigating Resistance of Deep Learning-based IDS against Adversaries using min-max Optimization
Rana Abou Khamis, Omair Shafiq, Ashraf Matrawy
With the growth of adversarial attacks against machine learning models, several concerns have emerged about potential vulnerabilities in designing deep neural network-based intrusi…