Integrating Machine Learning with Cryptography to Ensure Dynamic Data Security and Integrity

Abstract

Abstract: Keeping user data secure is very important in the modern era, as there are growing concerns on data privacy across the world. With very strict laws in place such as General data Protection Regulation (GDPR) in Europe and California Consumer Privacy Act (CCPA) in California, it has become a necessity for businesses and government agencies across the world to secure data in use, irrespective of whether it is at rest or in transit. Also, secure data transfer is a mandatory requirement for organizations which handle confidential data. Data privacy breach and data leak can impact the organizational value and reduce customer loyalty. In this paper, various methods of securing data transfer using a combination of Cryptography and advanced Machine Learning techniques have been discussed. The high-level idea is that ML should complement the existing cryptography methods used in practice, to build a robust and impeccable secure platform making it almost impossible for intruders to get into the system.