Individual privacy in data mining using fuzzy optimization

References

• Babaee Tirkolaee, E., I. Mahdavi, M. M. SeyyedEsfahani, and G. W. Weber. 2020. “A Hybrid Augmented Ant Colony Optimization for the Multi-trip Capacitated Arc Routing Problem Under Fuzzy Demands for Urban Solid Waste Management.” Waste Management & Research 38 (2): 156–172.
   PubMed Web of Science ®Google Scholar
• Bakhtavar, E., T. Prabatha, H. Karunathilake, R. Sadiq, and K. Hewage. 2020. “Assessment of Renewable Energy-Based Strategies for Net-Zero Energy Communities: A Planning Model Using Multi-objective Goal Programming.” Journal of Cleaner Production 272: 122886.
   Web of Science ®Google Scholar
• Bhuyan, H. K., and M. S. Huque. 2018. “Sub-feature Selection Based Classification.” 2018 2nd International Conference on Trends in Electronics and Informatics (ICOEI), 210–216. Tirunelveli, India: IEEE.
   Google Scholar
• Bhuyan, H. K., N. K. Kamila, and S. K. Dash. 2011. “An Approach for Privacy Preservation of Distributed Data in Peer-to-Peer Network Using Multiparty Computation.” International Journal of Computer Science Issues (IJCSI) 8 (4): 424.
   Google Scholar
• Bhuyan, H. K., L. R. Kumar, and K. R. Reddy. 2019. “Optimization Model for Sub-feature Selection in Data Mining.” 2019 International Conference on Smart Systems and Inventive Technology (ICSSIT), 1212–1216. Tirunelveli, India: IEEE.
   Google Scholar
• Bhuyan, H. K., M. Mohanty, and S. R. Das. 2012. “Privacy Preserving for Feature Selection in Data Mining Using Centralized Network.” International Journal of Computer Science Issues (IJCSI) 9 (3): 434.
   Google Scholar
• Bhuyan, H. K., and C. M. Reddy. 2018. “Sub-feature Selection for Novel Classification.” 2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT), 477–482. Coimbatore, India: IEEE.
   Google Scholar
• Cao, Y., M. Yoshikawa, Y. Xiao, and L. Xiong. 2019. “Errata on “Quantifying Differential Privacy in Continuous Data Release Under Temporal Correlations”.” IEEE Computer Architecture Letters 31 (11): 2234–2234.
   Google Scholar
• Chen, W., M. Panahi, and H. R. Pourghasemi. 2017. “Performance Evaluation of GIS-Based New Ensemble Data Mining Techniques of Adaptive Neuro-Fuzzy Inference System (ANFIS) with Genetic Algorithm (GA), Differential Evolution (DE), and Particle Swarm Optimization (PSO) for Landslide Spatial Modelling.” Catena 157: 310–324.
   Web of Science ®Google Scholar
• Christen, P., T. Ranbaduge, D. Vatsalan, and R. Schnell. 2018. “Precise and Fast Cryptanalysis for Bloom Filter Based Privacy-Preserving Record Linkage.” IEEE Transactions on Knowledge and Data Engineering 31 (11): 2164–2177.
   Web of Science ®Google Scholar
• Jahan, T., K. Pavani, G. Narsimha, and C. G. Rao. 2018. “A Data Perturbation Method to Preserve Privacy Using Fuzzy Rules.” In Bhateja V., Tavares J., Rani B., Prasad V., Raju K. (eds) Proceedings of the Second International Conference on Computational Intelligence and Informatics, 9–16. Singapore: Springer.
   Google Scholar
• Kamila, N. K., L. Jena, and H. K. Bhuyan. 2016. “Pareto-Based Multi-objective Optimization for Classification in Data Mining.” Cluster Computing 19 (4): 1723–1745.
   Web of Science ®Google Scholar
• Kumar, S., and K. K. Mohbey. 2019. “A Review on Big Data Based Parallel and Distributed Approaches of Pattern Mining.” Journal of King Saud University-Computer and Information Sciences. 1–24.
   Google Scholar
• Lamata, M. T., D. Pelta, and J. L. Verdegay. 2018. “Optimisation Problems as Decision Problems: The Case of Fuzzy Optimisation Problems.” Information Sciences 460-461: 377–388.
   Web of Science ®Google Scholar
• Langari, R. K., S. Sardar, S. A. A. Mousavi, and R. Radfar. 2020. “Combined Fuzzy Clustering and Firefly Algorithm for Privacy Preserving in Social Networks.” Expert Systems with Applications 141: 112968.
   Web of Science ®Google Scholar
• Lekshmy, P. L., and M. A. Rahiman. 2020. “A Sanitization Approach for Privacy Preserving Data Mining on Social Distributed Environment.” Journal of Ambient Intelligence and Humanized Computing 11 (7): 2761–2777.
   Web of Science ®Google Scholar
• Mendes, R., and J. P. Vilela. 2017. “Privacy-Preserving Data Mining: Methods, Metrics, and Applications.” IEEE Access 5: 10562–10582.
   Web of Science ®Google Scholar
• Pellungrini, R., L. Pappalardo, F. Pratesi, and A. Monreale. 2017. “A Data Mining Approach to Assess Privacy Risk in Human Mobility Data.” ACM Transactions on Intelligent Systems and Technology (TIST) 9 (3): 1–27.
   Web of Science ®Google Scholar
• Purohit, R., and D. Bhargava. 2017. “An Illustration to Secured Way of Data Mining Using Privacy Preserving Data Mining.” Journal of Statistics and Management Systems 20 (4): 637–645.
   Web of Science ®Google Scholar
• Rajesh, P., and F. H. Shajin. 2020. “A Multi-objective Hybrid Algorithm for Planning Electrical Distribution System.” International Information and Engineering Technology Association. 11: 66–82.
   Google Scholar
• Shajin, F. H., and P. Rajesh. 2020. “Trusted Secure Geographic Routing Protocol: Outsider Attack Detection in Mobile Ad Hoc Networks by Adopting Trusted Secure Geographic Routing Protocol.” International Journal of Pervasive Computing and Communications. https://doi.org/https://doi.org/10.1108/IJPCC-09-2020-0136
   Web of Science ®Google Scholar
• Sharma, S., J. Powers, and K. Chen. 2018. “PrivateGraph: Privacy-Preserving Spectral Analysis of Encrypted Graphs in the Cloud.” IEEE Transactions on Knowledge and Data Engineering 31 (5): 981–995.
   Web of Science ®Google Scholar
• Sin, G., Jianneng Cao Teo, and Vincent C. S. Lee. 2020. “DAG: A General Model for Privacy-Preserving Data Mining.” IEEE Transactions on Knowledge and Data Engineering 32 (1): 40–53.
   Web of Science ®Google Scholar
• Stojiljković, M. M. 2017. “Bi-level Multi-objective Fuzzy Design Optimization of Energy Supply Systems Aided by Problem-Specific Heuristics.” Energy 137: 1231–1251.
   Web of Science ®Google Scholar
• Transpire Online. 2020. “Horse Optimization Algorithm (HOA): Representative in Engineering Problem Application on Classification of the Smart Grid Stability.” Transpire Online 2020. Accessed December, 2020. https://transpireonline.blog/tag/feature-selection-based-on-an-improved-cat-swarm-optimization-algorithm-for-big-data-classification/.
   Google Scholar
• Zhao, L., L. Ni, S. Hu, Y. Chen, P. Zhou, F. Xiao, and L. Wu. 2018. “Inprivate Digging: Enabling Tree-Based Distributed Data Mining With Differential Privacy.” In IEEE INFOCOM 2018-IEEE Conference on Computer Communications, 2087–2095. Honolulu, HI, USA: IEEE.
   Google Scholar