most citedThe Threat of Adversarial Attacks on Machine Learning in Network Security -- A Survey

25 citations · 28 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2021★ 3 cited

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…

cs.CR2019★ 25 cited

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…