Article
Computer Science, Information Systems
Jyh-haw Yeh, Md Mashrur Arifin, Ning Shen, Ujwal Karki, Yi Xie, Archana Nanjundarao
Summary: In recent years, cloud storage has become a viable option for businesses, but it requires clients to relinquish control of their data. This paper presents a novel database model called ICDB, which allows clients to insert integrity codes and fake tuples, and verify the correctness, freshness, and completeness of queried data from the cloud.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Jiajia Jiang, Yushu Zhang, Youwen Zhu, Xuewen Dong, Liangmin Wang, Yong Xiang
Summary: Blockchain has the potential to impact various application areas, but it still faces technical challenges such as security and scalability. The emergence of cross-chain technologies addresses the issue of data storage pressure, but further research on data integrity in cross-chain interactions is needed. This paper proposes a decentralized cross-chain data integrity verification scheme and demonstrates its secure and accurate data sharing through theoretical and experimental analyses.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Engineering, Multidisciplinary
Haiyang Yu, Qi Hu, Zhen Yang, Huan Liu
Summary: Decentralized storage powered by blockchain is a new trend, but unqualified storage providers may face security threats, requiring continuous data integrity to be guaranteed, which can incur heavy burdens of both communication and computation.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2021)
Article
Immunology
Demetra S. Tsapepas, Kristen King, Syed Ali Husain, Miko E. Yu, Benjamin E. Hippen, Jesse D. Schold, Sumit Mohan
Summary: This article summarizes critical gaps in the OPTN/UNOS database and proposes ideas for improvement.
Article
Automation & Control Systems
Yuanyuan Xia, Shuangping Su, Housheng Su, Xinting Zhang, Weijie Luo, Wen Yang
Summary: This study investigates the security issue of distributed state estimation under data integrity attacks in wireless sensor networks. A detector based on statistical learning is designed to detect compromised estimates from neighboring sensors. Optimal estimator and stability condition for estimation error covariances are found for sensors equipped with the malicious data detector. The relationship between steady-state EEC and detector parameters is explored, and the performances of various detectors are verified through numerical simulations.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Computer Science, Hardware & Architecture
Yan Ding, Yanping Li, Wenjie Yang, Kai Zhang
Summary: This paper proposes a scheme called EDI-DA to verify data integrity in edge environments, addressing the issue of data replicas stored on edge servers facing damage. By extending and improving the scheme, EDI-DA enables batch auditing of multiple edge data replicas and supports full data dynamics. Security and performance analyses demonstrate the feasibility of the proposed scheme.
JOURNAL OF SYSTEMS ARCHITECTURE
(2022)
Article
Computer Science, Theory & Methods
Bo Li, Qiang He, Feifei Chen, Hai Jin, Yang Xiang, Yun Yang
Summary: Edge computing allows app vendors to deploy applications and data on distributed servers for better user experience. However, ensuring data integrity in this environment is challenging. Therefore, effectively auditing data integrity becomes a critical issue.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
(2021)
Article
Business
Tao Hong, Alex Hofmann
Summary: This article discusses potential cyberattacks on power systems, introduces a new research topic on data integrity attacks to outage management systems, and relates this topic to recent progress in state estimation, load forecasting, and outage prediction areas.
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
(2022)
Article
Environmental Sciences
Rytis Maskeliunas, Raimondas Pomarnacki, Van Khang Huynh, Robertas Damasevicius, Darius Plonis
Summary: To effectively monitor and handle big data from equipment linked to the power grid, it is important to continually gather information on power line integrity. Data transmission analysis and collection can be done with tools like digital power meters to perform predictive maintenance on power lines without specialized hardware. Neural network models, specifically deep learning, can be used safely and reliably for power line integrity analysis. We used a Q-learning based data analysis network for monitoring and analyzing power line integrity, with experiments conducted on a 32 km long power line. The proposed framework is applicable to traditional power lines, alternative energy parks, and large users like industries. The quantity of transferred data changes based on the problem and data packet size, and a power outage affects the amount of data collected from the line of interest. The Q-network successfully identified and classified simulated power outages, with low mean square error and a small number of errors and disturbances.
Article
Engineering, Civil
Dengzhi Liu, Yong Zhang, Weizheng Wang, Kapal Dev, Sunder Ali Khowaja
Summary: Internet of things (IoT) can be used in maritime transportation systems (MTS) to improve efficiency, prevent vessel collision, and reduce losses. However, traditional big data analysis methods cannot effectively process maritime traffic data, so data integrity checking is necessary. This paper proposes a flexible data integrity checking scheme with original data recovery in IoT-enabled MTS, which is proven to be secure and more efficient than previous schemes.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Hardware & Architecture
Chunpeng Ge, Willy Susilo, Joonsang Baek, Zhe Liu, Jinyue Xia, Liming Fang
Summary: This article explores a new security requirement for revocable attribute-based encryption schemes: integrity. It introduces a formal definition and security model for revocable attribute-based encryption with data integrity protection (RABE-DI) and proposes a concrete scheme that ensures confidentiality and integrity. The implementation result and performance evaluation demonstrate the efficiency and practicality of the proposed scheme.
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING
(2022)
Article
Computer Science, Information Systems
Guangyong Gao, Tingting Han, Zhao Feng, Min Wang, Zhihua Xia
Summary: This article proposes a data authentication scheme based on a double watermark for data security in wireless sensor networks (WSNs). The double watermark consists of a reversible watermark and an irreversible watermark. The scheme embeds the reversible watermark into the effective precision bit of data generated by group head data, and embeds the irreversible watermark into the flag bit using a defined array and the effective precision bit. The comprehensive performance of the proposed scheme outperforms that of existing schemes, as demonstrated by security analysis and experimental results.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Information Systems
Jing Huey Khor, Michail Sidorov, Ming Tze Ong, Shen Yik Chua
Summary: This article proposes a data protection protocol that ensures data integrity, reduces transaction fees, and prolongs battery life for IoT devices used with public blockchain networks. It presents a proof of concept using an ESP32S2 device to evaluate the performance of the proposed data storage protocol. The evaluation results demonstrate that data integrity can be achieved for low-power sensor nodes connecting to public blockchains via Wi-Fi network.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Information Systems
Shanshan Li, Chunxiang Xu, Yuan Zhang, Yicong Du, Anjia Yang, Xinsheng Wen, Kefei Chen
Summary: This article analyzes existing smart contract-based public data integrity verification schemes and identifies weaknesses in them. The fair arbitration mechanism in these schemes fails to promptly notify users of data corruption or loss, which does not meet the users' requirements. The conventional encrypted method used by existing schemes to ensure data confidentiality leads to additional storage costs for the cloud server due to varying ciphertexts for the same data. Users' devices, if poorly designed or backdoored, can compromise the security of the schemes. To address these issues, a new backdoor-resistant public data integrity verification scheme called ASSIST is proposed, which introduces a whistleblower entity to monitor the verification results and ensure timely notification of data corruption. ASSIST uses message-locked encryption to motivate the production of the same ciphertext for the same data and reduces storage costs. A cryptographic reverse firewall is deployed to prevent exfiltration from users' devices. Security proofs and performance evaluation demonstrate the efficiency and security of ASSIST.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Biochemistry & Molecular Biology
Fabio Hedayioglu, Emma J. Mead, Patrick B. F. O'Connor, Matas Skiotys, Owen J. Sansom, Giovanna R. Mallucci, Anne E. Willis, Pavel Baranov, C. Mark Smales, Tobias von der Haar
Summary: The study validates two experimental tools for assessing ribosome binding to mRNAs, highlighting the usefulness of polysome profile reconstructions in evaluating dataset quality.
NUCLEIC ACIDS RESEARCH
(2022)
