Cryptographic Data Security System for the Digital World Using SHA Algorithms
In the fast-shifting digital world of today, where data breaches, cyber-attacks, and unauthorized access are ever-increasing concerns, Secure Hash Algorithms (SHA) are still one of the bedrock cryptographic data security systems. As businesses and individuals rely on an increasing number of digital communications, cloud services, or decentralized systems like blockchain, the need for robust mechanisms that ensure integrity, authenticity and security of data has never been greater. SHA functions are designed to generate unique, fixed-length hash values for the respective input data, along with essential SHA properties of one-way transformation, collision resistance and determinism ensure that they are a critical component of securing modern security application. SHA algorithms are not just a means of encryption and/or decryption, but integrity of data, unique digital fingerprints and compromises of the system. The central utilization of SHA is the hashing of the input data to a hash value that is computationally infeasible to reverse or predict. With growing sophistication of cyber threats, the transition from SHA-1 to more secure algorithms such as SHA-256 and SHA-3 is indicative of the perpetual and increasing need to enhance cryptographic resilience against collision attacks, and the emerging reality of quantum computing. A thorough study of the SHA algorithms, framed as a Data Security System, is designed not just as a reference but also as an educational resource that incorporates discussions of historical matters, current usage of SHA on multiple platforms, and where feasible, the necessity to embrace modern digital cryptographic practices in a fast-paced, technologically evolving landscape.
Authors
- M. Chitra
- Hussain M. Mustafa (ORCID: https://orcid.org/0000-0003-3699-8653)
- Aditya Yadav (ORCID: https://orcid.org/0009-0004-9723-7473)
- Nigel Varghese
Institutions
- SRM Institute of Science and Technology (IN)
- SRM Dental College (IN)
Publication Details
- Journal
- Indian Journal of Computer Science
- Published
- 2025-04-05
- DOI
- https://doi.org/10.17010/ijcs/2025/v10/i2/175101
- Citations
- 1
- Primary Topic
- Face and Expression Recognition
- Type
- article
- Field-Weighted Citation Impact
- 1.28