A short review on Applications of Deep learning for Cyber security
It provides a review for researchers and practitioners in cybersecurity, but is incremental as it summarizes prior work.
This paper surveys existing deep learning applications in cybersecurity, covering areas like intrusion detection, malware classification, and spam detection, without presenting new results or numbers.
Deep learning is an advanced model of traditional machine learning. This has the capability to extract optimal feature representation from raw input samples. This has been applied towards various use cases in cyber security such as intrusion detection, malware classification, android malware detection, spam and phishing detection and binary analysis. This paper outlines the survey of all the works related to deep learning based solutions for various cyber security use cases. Keywords: Deep learning, intrusion detection, malware detection, Android malware detection, spam & phishing detection, traffic analysis, binary analysis.