A Review of Computer Vision Methods in Network Security

Network security has become an area of significant importance more than ever as highlighted by the eye-opening numbers data breaches, attacks on critical infrastructure, and malware/ransomware/cryptojacker that are reported almost every day. Increasingly, we relying networked infrastructure with advent IoT, billions devices will be connected to Internet, providing attackers opportunities exploit. Traditional machine learning methods have been frequently used in context network security. However, such based statistical features extracted from sources binaries, emails, packet flows. On other hand, recent years witnessed a phenomenal growth computer vision mainly driven advances convolutional neural networks. At glance, it is not trivial see how related Nonetheless, there amount work can applied for detecting or building solutions. In this paper, provide comprehensive survey under three topics; i) phishing attempt detection, ii) malware iii) traffic anomaly detection. We also discuss existing research gaps future directions, especially focusing community industry leverage exponential build much secure systems. Finally, review set commercial products which public information available explore effectively those conclude brief overview commonly domain.