Data integrity

Advanced hashing algorithms

August 5, 2026 by Sudhir K. Routray

Advanced hashing algorithms (AHAs) are crucial for modern cryptography. They can ensure data integrity, security, and efficient data management. In this article, we explore key aspects of these algorithms, including their fundamental principles, diverse applications, and ongoing research challenges. We delve into the intricacies of cryptographic hash functions, highlighting … [Read more...] about Advanced hashing algorithms

Challenges in simulation of digital twins: A review

May 28, 2025 by Dhanush L. Prakash, Nidhi B. C., Gopalakrishna H. D.

The digitalization of manufacturing processes is on the rise, marking the development of Industry 4.0 and the emergence of smart factories. Digital twins (DTs), which are digital replicas of physical assets or processes, are being utilized to enhance business applications. In the manufacturing sector, DTs can be created for asset-specific production lines or even entire … [Read more...] about Challenges in simulation of digital twins: A review

Privacy-preserving distributed learning: Techniques, applications, and future challenges

The rapid increase in data generated by connected devices has created a pressing need for privacy-preserving techniques in distributed learning. This article examines methods that enable collaborative machine learning (ML) while maintaining data security and user privacy. Key approaches such as federated learning (FL), differential privacy (DP), secure multiparty computation (SMPC), and homomorphic encryption (HE) are analyzed for their unique capabilities and various applications. FL facilitates model training across decentralized data sources, ensuring data remain local, while DP mitigates privacy risks by adding controlled noise. SMPC and HE support secure computations on encrypted data, maintaining confidentiality during processing. Despite their effectiveness, these techniques face challenges related to computational complexity, scalability, and regulatory compliance. The article reviews current advancements, practical implementations, and future directions, emphasizing the need for optimized, accessible solutions to enhance data security in distributed systems.

Data integrity

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