ISSUES AND CHALLENGES IN DATA SCIENCE SECURITY

Abstract

This study investigates the multifaceted landscape of data science security, addressing primary threats,
evaluating current security issues, exploring emerging technologies, and examining regulatory compliance.
Major targets are to discover any missing parts, to appraise the effectiveness of securing strategies, to investigate
technologies that deal with metadata exposure and computers’ mathematical operations without data decryption,
and to comprehend regulatory frameworks like GDPR (General Data Protection Regulation) and HIPAA (Health
Insurance Portability and Accountability Act). Output meets the subtleness of data security challenges,
illustrating the fact that an integrated view is required. To the best of our knowledge, no systematic review has
been done on how data Science and security and privacy overlap. Consequently, by summarizing and organizing
the existing research, this review seeks to investigate security and privacy research in the context of data
science . Additionally, we look into the papers that link data science security and privacy and the challenges that
these papers address.
The paper seeks to highlight the fact that companies should focus on conformity with regulations and ethical
requirements. Research in the future is set to focus on the scalability and actual installation of protective
measures linked to ethics.