Enhancing Data Security and Privacy through Advanced Encryption Techniques Secure Storage and Privacy-Preserving Analytics

Nivedhaa. N; K V Sri Varsha

Authors

Nivedhaa. N B. Tech AI & Data Science, Department of Artificial Intelligence and Data Science , Rajalakshmi Institute of Technology , Chennai, Tamilnadu , India Author
K V Sri Varsha II Year, BE. Computer Science & Engineering , Sri Krishna College of Engineering and Technology , Coimbatore, Tamilnadu , India. Author

Keywords:

Data Security, Advanced Encryption, Secure Cloud Storage, Privacy-Preserving Analytics, Data Masking, Quantum-Resistant Cryptography, Blockchain Security, Secure Data Transmission

Abstract

The exponential growth of digital data has led to increased cybersecurity threats, necessitating advanced techniques to secure data storage, protect privacy, and ensure secure data transmission. Encryption techniques such as homomorphic encryption, attribute-based encryption, and quantum-resistant cryptography play a vital role in securing sensitive information. Privacy-preserving analytics, including differential privacy and federated learning, allow for data analysis without compromising personal information. Additionally, blockchain-based access control mechanisms and secure data-sharing protocols improve data integrity and resilience against unauthorized access. This paper explores state-of-the-art methods in data security and privacy, analyzing their effectiveness and limitations. The study also discusses challenges and future directions in developing scalable and efficient data security frameworks.

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