Neural Network Approach of Combating the Data Security Issues

Abstract

One of the challenges the world is facing is cyber-attacks and threats such as data breaches, data leaks, etc., in which sensitive, confidential or protected data has been compromised. According to the information accessed by CERT (Indian Computer Emergency Response Team), in past five years, 47 incidents of data leak and 142 data breaches have occurred in India. Henceforth, cyber-security is emphasized more as economies of country, institutions, and individual lives are highly interconnected and growing more complex, protection of privacy and confidentiality has become crucial. Data analysis and the right implication of handling the data security issues are well addressed by ML algorithms. Many research indicators exhibited the comparison of various ML models to combat the data security issues. In this chapter, a novel approach of applying neural network for data security outperforms the data security issues. Self-Learning by the neural network models finds better pattern recognition for learning and the performance would be independent of any bias factors.