Publications

Went from absolutely knowing nothing about what research meant to publishing work at 2 IEEE conferences and a journal.

Forever grateful to my professor Dr.Sowmyarani CN for pushing me into doing this!

Here's a BTS of all the ideas and brain dump sessions with my co-author Nidhi :))

Enhanced k-anonymity model based on clustering to overcome temporal attack in privacy preserving data publishing
C. N. Sowmyarani, L. G. Namya, G. K. Nidhi, et al., in 2022 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT), 2022, pp. 1–6. doi:10.1109/CONECCT55679.2022.9865682.

This paper presents an enhanced k-anonymity model that uses clustering techniques to protect against temporal attacks in privacy-preserving data publishing. The approach improves upon traditional k-anonymity by considering temporal correlations in the data.

Link: https://ieeexplore.ieee.org/document/9865682

Analysis and optimization of clustering-based privacy preservation using machine learning
C. N. Sowmyarani, L. G. Namya, G. K. Nidhi, et al., in 2023 International Conference for Advancement in Technology (ICONAT), 2023, pp. 1–4. doi:10.1109/ICONAT57137.2023.10080207.

This work analyzes clustering-based approaches for privacy preservation and optimizes them using machine learning techniques. The study evaluates different clustering algorithms and their effectiveness in maintaining privacy while preserving data utility.

Link: https://ieeexplore.ieee.org/document/10080207

Score, arrange, and cluster: A novel clustering-based technique for privacy-preserving data publishing
C. N. Sowmyarani, L. G. Namya, G. K. Nidhi, et al., IEEE Access, vol. 12, pp. 79 861–79 874, 2024. doi:10.1109/ACCESS.2024.3403372.

This paper introduces a novel "Score, Arrange, and Cluster" technique for privacy-preserving data publishing. The method combines scoring mechanisms, data arrangement strategies, and advanced clustering to achieve better privacy guarantees compared to existing approaches.

Link: https://ieeexplore.ieee.org/document/10535110 or listen to an audio overview on NotebookLM