A Malware Classification Survey on Adversarial Attacks and Defences

Understand

As the number and complexity of malware attacks continue to increase, there is an urgent need for effective malware detection systems.

• While deep learning models are effective at detecting malware, they are vulnerable to adversarial attacks.
• Attacks like this can create malicious files that are resistant to detection, creating a significant cybersecurity risk.
• Recent research has seen the development of several adversarial attack and response approaches aiming at strengthening deep learning models' resilience to such attacks.