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Hadeel Alrubayyi, Moudy Sharaf Alshareef, Zunaira Nadeem, Ahmed M. Abdelmoniem and Mona Jaber
The hype of the Internet of Things as an enabler for intelligent applications and related promise for ushering accessibility, efficiency, and quality of service is met with hindering security and data privacy concerns. It follows that such IoT systems, w...
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Rezak Aziz, Soumya Banerjee, Samia Bouzefrane and Thinh Le Vinh
The trend of the next generation of the internet has already been scrutinized by top analytics enterprises. According to Gartner investigations, it is predicted that, by 2024, 75% of the global population will have their personal data covered under priva...
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Zacharias Anastasakis, Terpsichori-Helen Velivassaki, Artemis Voulkidis, Stavroula Bourou, Konstantinos Psychogyios, Dimitrios Skias and Theodore Zahariadis
Federated Learning is identified as a reliable technique for distributed training of ML models. Specifically, a set of dispersed nodes may collaborate through a federation in producing a jointly trained ML model without disclosing their data to each othe...
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Bin Cheng, Ping Chen, Xin Zhang, Keyu Fang, Xiaoli Qin and Wei Liu
With the rapid development of ubiquitous data collection and data analysis, data privacy in a recommended system is facing more and more challenges. Differential privacy technology can provide strict privacy protection while reducing the risk of privacy ...
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Suleiman Abahussein, Dayong Ye, Congcong Zhu, Zishuo Cheng, Umer Siddique and Sheng Shen
Online food delivery services today are considered an essential service that gets significant attention worldwide. Many companies and individuals are involved in this field as it offers good income and numerous jobs to the community. In this research, we...
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Konstantinos Demertzis, Konstantinos Rantos, Lykourgos Magafas, Charalabos Skianis and Lazaros Iliadis
Pursuing ?intelligent justice? necessitates an impartial, productive, and technologically driven methodology for judicial determinations. This scholarly composition proposes a framework that harnesses Artificial Intelligence (AI) innovations such as Natu...
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Liping Zhang, Jing Li and Song Li
A new spatial keyword group query method is proposed in this paper to address the existing issue of user privacy leakage and exclusion of preferences in road networks. The proposed query method is based on the IGgram-tree index and minimum hash set. To d...
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Liping Zhang, Xiaojing Zhang and Song Li
In view of the existing research in the field of k-nearest neighbor query in the road network, the incompleteness of the query user?s preference for data objects and the privacy protection of the query results are not considered, this paper proposes a mu...
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Yan Yan, Zichao Sun, Adnan Mahmood, Fei Xu, Zhuoyue Dong and Quan Z. Sheng
Statistical partitioning and publishing is commonly used in location-based big data services to address queries such as the number of points of interest, available vehicles, traffic flows, infected patients, etc., within a certain range. Adding noise per...
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Xin Yao, Juan Yu, Jianmin Han, Jianfeng Lu, Hao Peng, Yijia Wu and Xiaoqian Cao
Generating differentially private synthetic human mobility trajectories from real trajectories is a commonly used approach for privacy-preserving trajectory publishing. However, existing synthetic trajectory generation methods suffer from the drawbacks o...
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