25 citations · 34 across the 5 of their papers we have counts for
5 papers
Cybersecurity Challenge Analysis of Work-from-Anywhere (WFA) and Recommendations guided by a User Study
Mohammed Mahyoub, Ashraf Matrawy, Kamal Isleem +1
Many organizations were forced to quickly transition to the work-from-anywhere (WFA) model as a necessity to continue with their operations and remain in business despite the restr…
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…
The Threat of Adversarial Attacks on Machine Learning in Network Security -- A Survey
Olakunle Ibitoye, Rana Abou-Khamis, Mohamed el Shehaby +2
Machine learning models have made many decision support systems to be faster, more accurate, and more efficient. However, applications of machine learning in network security face…
Analyzing Adversarial Attacks Against Deep Learning for Intrusion Detection in IoT Networks
Olakunle Ibitoye, Omair Shafiq, Ashraf Matrawy
Adversarial attacks have been widely studied in the field of computer vision but their impact on network security applications remains an area of open research. As IoT, 5G and AI c…