EVALUATING CRYPTOGRAPHIC PROTOCOLS FOR DATA SECURITY IN UNIFIED DATA MINING

Abstract

Data mining has become indispensable in extracting valuable insights from vast datasets across various domains. Unified data mining, which integrates data from disparate sources, enhances the effectiveness of data analysis. However, the amalgamation of data from diverse origins raises significant security concerns, particularly regarding the privacy and confidentiality of sensitive information. Cryptographic protocols play a crucial role in ensuring data security in unified data mining environments. This research paper evaluates different cryptographic protocols in terms of their suitability and effectiveness in safeguarding data integrity, confidentiality, and privacy in unified data mining scenarios. Various cryptographic techniques such as homomorphic encryption, secure multiparty computation, and differential privacy are analyzed based on their strengths, weaknesses, and applicability in unified data mining contexts. Additionally, the paper discusses the challenges and trade-offs associated with implementing these protocols and provides insights into future research directions aimed at enhancing data security in unified data mining.