Implications Of Machine Learning In Cyber Security

Cybersecurity is positioned to improve security concerns in cyberspace by utilizing potential algorithms. Cyber networks and platforms are prone to cyber attacks. The recent survey reveals that, 45% of cyber attacks has grew in the last 5 years. Identifying the threats like malware, ransomware and network breach is challenging, since the threats are hetrogenity in nature. Organizations are facing a daunting challenge of dealing with the millions of new attacks a day. Conventional security analysis fails to identify the threats due to the rapid development in new attacks and variants. Cyber Security may be measured and evaluated against multiple threats. While they are not the only method for securing, assessing the vulnerability and information leakage, automating the network security and platform play an integral role in the cyber space.Machine learning is a powerful technique to develop a system, which adapts to the data stream. In order to deal with huge volume of data more efficiently and precisely, machine learning algorithms will be used to distinguish threats and identifying the infected hosts. However, certain intrisic characteristics of machine learning algorithms makes the implementation more challenging. The agenda of the talk will be focused on the mitigation of cyber attacks with the help of machine learning approaches by automation.