Jul 2026· Journal of Data, Information and Management· Vol 8, pp. 171 - 191· 0 citations· 50 references
TL;DR
The results demonstrate that SA-LDP-DW supports responsible data sharing, data governance, and privacy-aware data analytics, enabling privacy protection, ownership verification, and reliable analytical utility for real-world data-driven applications.
In today’s era of big data, personal privacy is increasingly at risk due to widespread data sharing. Mobile applications often collect excessive personal information, while advanced analytics can sometimes lead to biased or discriminatory practices. These challenges create an urgent need for secure, privacy-preserving...
Chaitanya Tumma, Supraja Ayyamgari, Charan Thumma et al.· 2026 International Conferenc...· 0 citations
The experiment showed that Autoencoder Based Federated Learning was a scalable, secure, and privacy-efficient solution to applications tailored for healthcare, finance, and other sensitive data environments.
Guman Singh Chauhan, venkata Surya Teja Gollapalli, Kannan Srinivasan et al.· Journal of Science & Technol...· 0 citations
A five-dimensional policy package is proposed that reinforces regulatory drivers, institutionalises trust-repair mechanisms, leverages trauma-induced learning effects, optimises transmission pathways, and implements full-cycle collaborative governance, thereby offering a systemic intervention framework to resolve the d...
Ting Zhang, Zhong-Xian Duan· Humanities and Social Scienc...· 0 citations
The findings indicate that unifying adaptive privacy preservation with decentralized integrity auditing yields a more complete cloud-security posture than either mechanism alone, and the paper outlines the empirical validation, including full-scale testbed experiments, required before deployment.
Jayakumar D, M. Ramamoorthy· International journal of com...· 0 citations
A privacy-aware Federated Data Engineering framework that integrates federated learning, distributed data engineering, and secure model aggregation for cross-enterprise analytics and incorporates privacy-enhancing technologies to ensure confidentiality, integrity, and transparency is presented.
Karen Spärck Jones, Donald Michie· International Journal of Dat...· 0 citations
The Privacy Index is introduced, a unified metric designed to aggregate multiple privacy-related factors into a single, interpretable score that integrates the validation of established privacy models, detection of anonymization techniques, and estimation of re-identification risk under different attacker assumptions.
José A. Gameiro, J. Oliveira, João Rafael Almeida· International Conference on...· 0 citations
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