Security analysis for machine learning and image processing related information systems

Abstract

With the exponential increase in data available online, the need for its safeguarding is manifold. Privacy models have been built to give sophistication in the expense of data in every aspect. The information has become the new asset. Machine Learning and Image Processing techniques replace traditional modes of data privacy. There is a need to involve autonomous systems in privacy mechanisms. From the storage of data to its analysis, there is always a threat of data theft or malpractice from intruders. A novel model based on data fragmentation and increased associates in the authentication system which ensures enhanced security of information is proposed. The model brings out layered protection of data using autonomous systems. This paper analyzes key Machine Learning and Image Processing based privacy models and contrasts them. Challenges related to data privacy and security are also discussed.