NAttack! Adversarial Attacks to bypass a GAN based classifier trained to detect Network intrusion

Exploring foci of: doi.org NAttack! Adversarial Attacks to bypass a GAN based classifier trained to detect Network intrusion May 2020 • Aritran Piplai, Sai Sree Laya Chukkapalli, Anupam Joshi With the recent developments in artificial intelligence and machine learning, anomalies in network traffic can be detected using machine learning approaches. Before the rise of machine learning, network anomalies which could imply an attack, were detected using well-crafted rules. An attacker who has knowledge in the field of cyber-defence could make educated guesses to sometimes accurately predict which particular features of network traffic data the cyber-defence mechanism is looking at. With this information, t… Open Article Page

Computer Science Adversarial Machine Learning Artificial Intelligence Machine Learning Generative Adversarial Network Generative Grammar Deep Learning Anomaly Detection Computer Security Open Article