Towards Efficient and Privacy-Preserving Interval Skyline Queries Over Time Series Data

Author:

Zhang Songnian1ORCID,Ray Suprio1ORCID,Lu Rongxing1ORCID,Zheng Yandong1ORCID,Guan Yunguo1ORCID,Shao Jun2ORCID

Affiliation:

1. Faculty of Computer Science, University of New Brunswick, Fredericton, Canada

2. School of Computer and Information Engineering, Zhejiang Gongshang University, Hangzhou, China

Funder

Natural Sciences and Engineering Research Council of Canada

Natural Science Foundation of Zhejiang Province

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. CoDetect: cooperative anomaly detection with privacy protection towards UAV swarm;Science China Information Sciences;2024-04-22

2. Speedy Privacy-Preserving Skyline Queries on Outsourced Data;Lecture Notes in Computer Science;2024

3. Low-overhead Privacy-preserving Location-based Skyline Query;2023 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom);2023-12-21

4. SecDR: Enabling Secure, Efficient, and Accurate Data Recovery for Mobile Crowdsensing;IEEE Transactions on Dependable and Secure Computing;2023

5. On the Security of “LSFL: A Lightweight and Secure Federated Learning Scheme for Edge Computing";IEEE Transactions on Information Forensics and Security;2023

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