Published Paper Details:

Machine learning has moved from the lab to the forefront of operational systems during the past several years. Machine learning is used daily by Amazon, Google, and Facebook to enhance user experiences, recommend products, or help people connect socially through new applications and enable personal connections. The potent capability of machine learning is also present for cyber security. Machine learning will be used by cyber security to enhance malware detection, priorities events, identify breaches, and notify enterprises of security risks. Advanced threats and targeting, including organization profiling, infrastructure vulnerabilities, and potentially interconnected security breaches and exploits, can be detected using machine learning. The landscape of cyber security may be drastically altered by machine learning. As many as 3.75 million new samples can be represented by malware alone every hour. Conventional methods of malware analysis and detection are unable to keep up with evolving threats. Cyber-attacks are being delivered at frightening rates thanks to new attacks and clever malware that may avoid network and end-point detection. To combat the expanding malware problem, new methods like machine learning must be used. This study explains how cyber defense analysts may utilize machine learning to find and highlight sophisticated malware. The findings of our preliminary study are presented, and future research to advance machine learning is discussed.