Smart City Gnosys

Smart city article details

Title	Improved Privacy-Ensuring Data-Fusion And Service Recommendation For Users In Smart Cities
ID_Doc	30741
Authors	Sarim M.; Ansari M.S.; Kanwal N.; Asghar M.
Year	2021
Published	2021 IEEE International Smart Cities Conference, ISC2 2021
DOI	http://dx.doi.org/10.1109/ISC253183.2021.9562777
Abstract	Smart cities are the most notable examples of cyberphysical-social systems, and produce an enormous amount of industrial data related to enterprise businesses, healthcare facilities, transportation, security & surveillance, pollution and carbon emissions etc. Such multi-source data is inherently heterogeneous in nature, and therefore in order to achieve reasonably effective and efficient utilization of such data we almost always require data fusion and mining. However, such data analyses could mean the breach of the privacy of the individuals if the user data is used as it is. Privacy-preserving information consolidation and analysis approaches are therefore being developed for such use cases. In this work, an improved privacy-ensuring data fusion and service recommendation approach targeted towards users in smart city environments is presented. The approach starts with first obfuscating user-data to eliminate user-specific information (thereby ensuring user privacy), and creates equivalent time-aware indices corresponding to the user data, which are forwarded to the cloud for data fusion and service recommendation. Extensive experiments, performed on a real-world dataset, demonstrate the superiority of the proposed approach over its contemporary counterparts.
Author Keywords	Data fusion and prediction; locality-sensitive hashing; privacy; smart city; spatial-temporal context

Similar Articles

Id	Similarity	Authors	Title	Published
43141	0.899	Qi, LY; Hu, CH; Zhang, XY; Khosravi, MR; Sharma, S; Pang, SN; Wang, T	Privacy-Aware Data Fusion And Prediction With Spatial-Temporal Context For Smart City Industrial Environment	IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 17, 6 (2021)
43171	0.894	Sei Y.	Privacy-Preserving Data Collection And Analysis For Smart Cities	Human-Centered Services Computing for Smart Cities: IEICE Monograph (2024)
1725	0.873	Khan M.A.	A Formal Method For Privacy-Preservation In Cognitive Smart Cities	Expert Systems, 39, 5 (2022)
43147	0.872	Zhang, F; Lee, VE; Jin, RM; Garg, S; Choo, KKR; Maasberg, M; Dong, LJ; Cheng, C	Privacy-Aware Smart City: A Case Study In Collaborative Filtering Recommender Systems	JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, 127 (2019)
43121	0.866	Anjum, A; Ahmed, T; Khan, A; Ahmad, N; Ahmad, M; Asif, M; Reddy, AG; Saba, T; Farooq, N	Privacy Preserving Data By Conceptualizing Smart Cities Using Midr-Angelization	SUSTAINABLE CITIES AND SOCIETY, 40 (2018)
10566	0.865	Jena R.; Kumar M.; Mallela I.R.; Das A.; Vashishtha S.; Agarwal N.	Artificial Intelligence-Driven Solutions For Privacy And Security In Smart City Data Management Systems For Smart Cities	Proceedings of the 2024 13th International Conference on System Modeling and Advancement in Research Trends, SMART 2024 (2024)
709	0.864	Zheng, X; Tian, L; Luo, GC; Cai, ZP	A Collaborative Mechanism For Private Data Publication In Smart Cities	IEEE INTERNET OF THINGS JOURNAL, 7, 9 (2020)
14757	0.861	Sampaio S.; Sousa P.R.; Martins C.; Ferreira A.; Antunes L.; Cruz-Correia R.	Collecting, Processing And Secondary Using Personal And (Pseudo)Anonymized Data In Smart Cities	Applied Sciences (Switzerland), 13, 6 (2023)
43095	0.859	Peterson M.; Fröding B.	Privacy In A Smart City	Etikk i Praksis, 18, 1 (2024)
47883	0.859	Tariq F.; Afzaal A.; Anjum M.J.; Kanwal F.; Bashir K.; Shaheen M.	Security And Privacy Preservation In Smart Cities During Security Surveillance: A Mapping Study	Applied Computational Intelligence and Soft Computing, 2025, 1 (2025)