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
Engineering, Multidisciplinary
Lihua Yin, Jiyuan Feng, Hao Xun, Zhe Sun, Xiaochun Cheng
Summary: The paper introduces a new hybrid privacy-preserving method for addressing data leakage threats in existing federated learning training processes. It utilizes advanced functional encryption algorithms and local Bayesian differential privacy to enhance data protection, while also implementing Sparse Differential Gradient to improve transmission and storage efficiency.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2021)
Article
Computer Science, Information Systems
Jianfei Sun, Guowen Xu, Tianwei Zhang, Hu Xiong, Hongwei Li, Robert H. Deng
Summary: Benefiting from the powerful computing and storage capabilities of cloud services, data sharing in the cloud has been widely used in various applications. However, concerns about data privacy breaches have arisen due to outsourcing data to untrusted cloud. To address this issue, this article proposes an Efficient, Scalable and Privacy-preserving Data sharing framework over encrypted cloud dataset (ESPD). Unlike previous works, ESPD supports sharing target data to multiple users with distinct secret keys and maintains a constant ciphertext length. Security analysis and real-world experiments demonstrate the desirable performance of ESPD compared to other similar schemes.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2023)
Article
Computer Science, Hardware & Architecture
Chunpeng Ge, Zhe Liu, Jinyue Xia, Liming Fang
Summary: Cloud computing relies on massive storage and computing capabilities, making secure data sharing crucial. Recent IB-BPRE schemes aim to address this, but involve users in the complex key sharing process. To simplify this, a new RIB-BPRE scheme allows proxies to revoke specific users from the re-encryption key, making it efficient and practical.
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING
(2021)
Article
Computer Science, Information Systems
Tian Li, Huaqun Wang, Debiao He, Jia Yu
Summary: This article presents a blockchain-based privacy-preserving and rewarding private data-sharing scheme (BPRPDS) for IoT. By using blockchain technology to build an anonymous trading system, it addresses the issues of privacy, security, and access control in sharing private data. The paper introduces the implementation of BPRPDS and demonstrates its efficiency and practicality through performance analysis and experimental results.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Wenle Bai, Aoran Huang
Summary: This paper proposes a privacy-preserving collaborative sharing protocol based on the Paillier cryptosystems in fog-enhanced IoT. The protocol ensures fair cost-sharing without communication between users and accurately transmits stored data to users based on their requests without violating their personal privacy.
Article
Computer Science, Information Systems
Jun Feng, Hu Xiong, Jinhao Chen, Yang Xiang, Kuo-Hui Yeh
Summary: The cooperative works between connected smart devices in the IIoT have greatly improved productivity and economics for the conventional industry. However, the introduction of the communication network also brings unprecedented cyber threats to the budding IIoT. To address this, an efficient and fully secure data sharing work called DS-SRL is proposed, which enables flexible access control and direct revocation approach for handling potential security issues. The DS-SRL scheme has the advantages of low computational and dissemination costs, high flexibility, scalability, and security, making it suitable for IIoT applications. Detailed performance evaluation confirms the feasibility, efficiency, and effectiveness of the DS-SRL work.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Information Systems
Yangyang Bao, Weidong Qiu, Peng Tang, Xiaochun Cheng
Summary: This paper proposes an ERPF-DS-KS scheme to address the data security and privacy issues in cloud-assisted MIoT, realizing efficient and fine-grained access control and ciphertext keyword search. It provides data authenticity through a pseudo identity-based signature mechanism and enables flexible indirect revocation of malicious data users.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2022)
Article
Computer Science, Information Systems
Hongcheng Xie, Yu Guo, Xiaohua Jia
Summary: This article presents a privacy-preserving-location-based data query scheme in fog-enhanced sensor networks by utilizing somewhat homomorphic encryption technology to protect user privacy while allowing cloud and fog devices to collect sensor data from specific areas. It implements a secure and efficient matched data extraction scheme and system prototype, and evaluates it in the software guard extension environment.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Guangquan Xu, Chen Qi, Wenyu Dong, Lixiao Gong, Shaoying Liu, Si Chen, Jian Liu, Xi Zheng
Summary: With the increasing adoption of IoT in people's lives, the limitations of traditional medical systems, such as privacy disclosure and system isolation, are becoming evident. To address these issues, we propose a privacy-preserving medical data-sharing scheme based on blockchain with an authorization mechanism and attribute-based encryption. Our scheme breaks system boundaries and facilitates data sharing among multiple medical institutions. We also provide a prototype tool implemented on Ethereum, showing that our scheme effectively balances medical data privacy and the need for data sharing.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2023)
Article
Computer Science, Information Systems
Xin Wei, Yong Yan, Shaoyong Guo, Xuesong Qiu, Feng Qi
Summary: As IoT services become more advanced, data sharing among different IoT systems is increasingly popular. To address the trust and security challenges faced by traditional IoT systems that rely on central clouds for data storage and access, we propose a multicenter data management framework based on blockchain to create a trusted environment for data sharing. We also introduce an attribute-based encryption algorithm that can be used for multicenter scenarios and shift the data management to blockchain instead of a central server. Additionally, we design an obfuscating policy to offload encryption computations to the cloud, reducing the computational burden on IoT devices.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Shancang Li, Shanshan Zhao, Geyong Min, Lianyong Qi, Gang Liu
Summary: The emerging technologies in IoT, such as smart sensors, 5G/6G wireless communication, and artificial intelligence, have revolutionized business operations by enabling efficient and privacy-preserving collection and transmission of real-time data. However, privacy concerns remain a major challenge. This study proposes a lightweight privacy-preserving scheme based on homomorphic encryption in IoT, effectively protecting user privacy through computationally efficient algorithms.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Mingzhe Li, Jingrou Wu, Wei Wang, Jin Zhang
Summary: The article presents an online framework for assigning tasks to workers in a fully distributed manner while protecting location privacy. The system uses homomorphic encryption to protect the location privacy of both workers and tasks, and proposes novel wait-and-decide and proportional-backoff mechanisms to increase the number of assigned tasks efficiently and in a privacy-preserving manner.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Chang Xu, Ruijuan Wang, Liehuang Zhu, Chuan Zhang, Rongxing Lu, Kashif Sharif
Summary: Searchable symmetric encryption (SSE) allows keyword search on encrypted data. Dynamic searchable symmetric encryption (DSSE) enables data updating. Existing DSSE schemes suffer from keyword pair result pattern (KPRP) leakage. We propose the first DSSE scheme that achieves strong privacy-preserving conjunctive keyword search.
IEEE TRANSACTIONS ON BIG DATA
(2023)
Article
Computer Science, Information Systems
Yange Chen, Suyu He, Baocang Wang, Pu Duan, Benyu Zhang, Zhiyong Hong, Yuan Ping
Summary: Industrial Internet of Things (IIoT) is changing traditional industries with the development of big data and deep learning. However, the lack of large-scale datasets can lead to performance issues and data leakage. Privacy-preserving federated learning schemes have been proposed, but security issues remain. In this article, the security of a scheme called DeepPAR is analyzed and an improved scheme is proposed to address the security vulnerabilities. Performance analysis illustrates the security and accuracy of the improved scheme.
IEEE INTERNET OF THINGS JOURNAL
(2022)
