Article
Computer Science, Information Systems
Yili Jiang, Kuan Zhang, Yi Qian, Liang Zhou
Summary: This article introduces a novel optimization framework for single query to minimize privacy cost while ensuring personalized DP and customized data utility. By introducing a reinforcement learning-based algorithm, the optimization problem can be efficiently solved to enhance the tradeoff between privacy preservation and data utility.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Artificial Intelligence
Yinglong Li, Weiru Liu, Yihua Zhu, Hong Chen, Hongbing Cheng, Tieming Chen, Ping Hu, Ruohong Huan
Summary: This article proposes two privacy-aware fuzzy query processing schemes based on fuzzy theory and introduces linguistic range variables, fuzzy overlap information, and its recovery mechanism. It also devises two distributed privacy-aware fuzzy range query processing algorithms. The approaches aim to provide optimal performances in terms of privacy protection, reliability, energy efficiency, and real-time response.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Computer Science, Information Systems
Cong Peng, Min Luo, Huaqun Wang, Muhammad Khurram Khan, Debiao He
Summary: This article proposes an efficient privacy-preserving multidimensional data aggregation scheme called PMDA for IoT. Through the use of homomorphic encryption method and signature mechanism, the scheme ensures nonrepudiation of device data and verification efficiency at edge nodes.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Dapeng Wu, Meiyu Sun, Puning Zhang, Yanli Tu, Zhigang Yang, Ruyan Wang
Summary: Demand-oriented data service can conveniently and quickly provide physical entity information for IoT users. Traditional cloud-oriented data service architecture is not suitable for state time-varying and privacy-sensitive entity data in IoT. Edge-based architecture lacks global service function but can alleviate problems with cloud services. Existing demand-oriented data service ignores the characteristics of thousands of people have thousands of faces and the implicit intents of users, resulting in limited service quality and weak user experience. To solve these problems, a personalized secure demand-oriented data service scheme is proposed.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Information Systems
Hassan Mahdikhani, Rongxing Lu, Jun Shao, Ali Ghorbani
Summary: The article proposes a new efficient and privacy-preserving range query scheme in fog-based IoT, utilizing decomposition technique and symmetric homomorphic encryption for privacy protection and improved query efficiency. Security analysis shows the scheme is privacy preserving, and performance evaluations demonstrate its higher efficiency compared to previous schemes in terms of computational overhead and communication complexity.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Telecommunications
Yizhou Shen, Shigen Shen, Qi Li, Haiping Zhou, Zongda Wu, Youyang Qu
Summary: This article presents evolutionary privacy preservation learning strategies for an edge computing-based IoT data sharing scheme, addressing the issue of malicious requests and proposing a new algorithm for optimal learning strategy.
DIGITAL COMMUNICATIONS AND NETWORKS
(2023)
Article
Computer Science, Information Systems
Lichuan Ma, Qingqi Pei, Lu Zhou, Haojin Zhu, Licheng Wang, Yusheng Ji
Summary: The study proposed a federated data cleaning protocol, FedClean, for edge intelligence scenarios to achieve data cleaning without compromising data privacy. By generating Boolean shares of data and privately computing AVF scores, abnormal data entries are filtered out through a bitonic sorting network.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Automation & Control Systems
Shuai Shang, Xiong Li, Ke Gu, Lei Li, Xiaosong Zhang, Vijayakumar Pandi
Summary: This article proposes a privacy-preserving data aggregation scheme for edge-supported IIoT, which utilizes the Paillier cryptosystem and ECDSA signature to improve efficiency and ensure data integrity and authentication among entities, while achieving differential privacy protection.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Computer Science, Information Systems
Jiawei Zhang, Jianfeng Ma, Yanbo Yang, Ximeng Liu, Neal N. Xiong
Summary: This article proposes a revocable and privacy-preserving decentralized data-sharing framework for secure data sharing in IoT systems. It uses a large universe and multiauthority CP-ABE scheme to protect user attribute privacy and resist key escrow, while also enabling the tracing and revocation of traitors and ensuring data integrity.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Ons Aouedi, Alessio Sacco, Kandaraj Piamrat, Guido Marchetto
Summary: Recent medical applications have benefited from the use of Machine Learning (ML) models to assist expert decisions, leading to significant innovations in radiology, pathology, genomics, and overall healthcare systems. However, issues related to data scarcity, privacy, and information exchange hinder the full potential of ML. Federated Learning (FL) has emerged as a valuable approach in the medical field, allowing decentralized training of models while preserving privacy-sensitive medical data.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2023)
Review
Computer Science, Hardware & Architecture
Raihan Ur Rasool, Hafiz Farooq Ahmad, Wajid Rafique, Adnan Qayyum, Junaid Qadir
Summary: The Internet of Medical Things (IoMT) enhances the scalability, efficiency, reliability, and accuracy of healthcare services, but the resource-constrained nature of these devices makes them vulnerable to security and privacy threats.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2022)
Article
Computer Science, Information Systems
Juntao Gao, Xinxiang Liu, Xuelian Li, Baocang Wang
Summary: This article encrypts attribute values using methods such as Bloom filters to effectively prevent inference attacks, while hiding user search patterns by multiplying by a large number to protect user privacy. The simulation evaluation showed better performance compared to existing schemes, demonstrating the effectiveness of the proposed encryption methods in protecting user data.
IEEE SYSTEMS JOURNAL
(2022)
Article
Computer Science, Information Systems
Shuai Shang, Xiong Li, Rongxing Lu, Jianwei Niu, Xiaosong Zhang, Mohsen Guizani
Summary: This article proposes a privacy-preserving multidimensional range query scheme, called Edge-PPMRQ, for edge-supported Industrial Internet of Things (IIoT). By designing a novel range division algorithm, efficient multidimensional range query is achieved, and detailed security analysis and performance evaluation are conducted.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Fuyuan Song, Zheng Qin, Liang Xue, Jixin Zhang, Xiaodong Lin, Xuemin Shen
Summary: This article introduces a scheme for encrypted spatial keyword search in a cloud computing environment. By designing a geometric range query scheme and a multidimensional spatial keyword similarity search scheme, the privacy of data owners and search users is protected while improving query efficiency.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Mahit Kumar Paul, Md Rabiul Islam, A. H. M. Sarowar Sattar
Summary: This study introduces a four-stage data perturbation approach called NRoReM to achieve a balance between privacy protection and data utility, demonstrating better protection of individual privacy and data utility in experiments.
JOURNAL OF INFORMATION SECURITY AND APPLICATIONS
(2021)