Detecting the Security Level of Various Cryptosystems Using Machine Learning Models

Project Code :TCMAPY478

Objective

The aim of the project is to automate the detection of security levels of various cryptosystems using machine learning.

Abstract

The security of digital data has become a crucial concern as a result of recent advances in multimedia technology. Researchers tend to focus their efforts on changing existing protocols to overcome the flaws of present security mechanisms. Several proposed encryption algorithms, however, have been proven insecure during the last few decades, posing serious security risks to sensitive data.

Using the most appropriate encryption technique to protect against such assaults is critical, but which algorithm is most suited in any given case will depend on the type of data being protected. However, testing potential cryptosystems one by one to find the best option can take up an important processing time. For a fast and accurate selection of appropriate encryption algorithms, we propose a security level detection approach for image encryption algorithms by incorporating a support vector machine (SVM).

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.