Neural Networks and Deep Learning in Cyber Security

In the last years, the deep learning (DL) technology using various deep neural network models / architectures became the state-of-the-art in Machine Learning (ML) and Artificial Intelligence (AI), its applications reaching better performances than humans in more and more domains. While traditional ML techniques were mainly based on certain mandatory initial “hand-crafted” feature extraction and engineering phase, the new DL approach is automatically performing this step of specific feature representations extraction directly from the raw input training samples. This intrinsic ability makes it applicable to various issues that cyber security is currently dealing with, such as: intrusion detection, malware classification and detection, spam and phishing detection and binary analysis. In this paper we are intending a brief overview of artificial neural networks and some examples of deep learning based solutions in cyber security.