82 citations · 112 across the 4 of their papers we have counts for
5 papers
Black-box Adversarial Transferability: An Empirical Study in Cybersecurity Perspective
Khushnaseeb Roshan, Aasim Zafar
The rapid advancement of artificial intelligence within the realm of cybersecurity raises significant security concerns. The vulnerability of deep learning models in adversarial at…
Untargeted White-box Adversarial Attack with Heuristic Defence Methods in Real-time Deep Learning based Network Intrusion Detection System
Khushnaseeb Roshan, Aasim Zafar, Sheikh Burhan Ul Haque
Network Intrusion Detection System (NIDS) is a key component in securing the computer network from various cyber security threats and network attacks. However, consider an unfortun…
A Novel Deep Learning based Model to Defend Network Intrusion Detection System against Adversarial Attacks
Khushnaseeb Roshan, Aasim Zafar, Shiekh Burhan Ul Haque
Network Intrusion Detection System (NIDS) is an essential tool in securing cyberspace from a variety of security risks and unknown cyberattacks. A number of solutions have been imp…
Using Kernel SHAP XAI Method to optimize the Network Anomaly Detection Model
Khushnaseeb Roshan, Aasim Zafar
Anomaly detection and its explanation is important in many research areas such as intrusion detection, fraud detection, unknown attack detection in network traffic and logs. It is…
Utilizing XAI technique to improve autoencoder based model for computer network anomaly detection with shapley additive explanation(SHAP)
Khushnaseeb Roshan, Aasim Zafar
Machine learning (ML) and Deep Learning (DL) methods are being adopted rapidly, especially in computer network security, such as fraud detection, network anomaly detection, intrusi…