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Journal articles on the topic 'Privacy-based data sharing'

Author: Grafiati

Published: 5 June 2025

Last updated: 2 August 2025

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1

Kumar.R, Dr Prasanna, Porselvan G, Prem Kumar S, and Robinlash F. "Security and Privacy Based Data Sharing in Cloud Computing." International Journal of Innovative Research in Engineering & Management 5, no. 1 (2018): 42–49. http://dx.doi.org/10.21276/ijirem.2018.5.1.9.

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Pooja, Pooja. "Privacy Protection and Intrusion Avoidance for Cloudlet-Based Medical Data Sharing." International Journal of Trend in Scientific Research and Development Volume-2, Issue-4 (2018): 2529–33. http://dx.doi.org/10.31142/ijtsrd15628.

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M, Divya, and Singaravel Dr.G. "Block Chain Technology for Privacy Protection for Cloudlet-based Medical Data Sharing." Bonfring International Journal of Software Engineering and Soft Computing 9, no. 2 (2019): 43–46. http://dx.doi.org/10.9756/bijsesc.9021.

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prasanna,, G. Laxmi. "PRIVACY PRESERVING DATA SHARING CLOUD-BASED HEALTHCARE SYSTEMS." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 01 (2025): 1–9. https://doi.org/10.55041/ijsrem40474.

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The integration of cloud computing into healthcare systems has revolutionized data management by enabling seamless data sharing and enhanced accessibility, thereby improving patient outcomes and operational efficiency. However, the sensitive nature of healthcare data necessitates robust privacy-preserving mechanisms to protect patient confidentiality. This paper explores state-of-the-art techniques such as cryptography, data anonymization, and secure access control, which are tailored to address privacy challenges in healthcare environments. It also critically evaluates existing frameworks, id

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Dr., Vinod Varma Vegesna. "Secure and Privacy-Based Data Sharing Approaches in Cloud Computing for Healthcare Applications." Mediterranean Journal of Basic and Applied Sciences (MJBAS) 4, no. 4 (2020): 194–209. https://doi.org/10.46382/MJBAS.2020.4409.

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The cloud framework is extensively employed in the medical industry for a broad range of applications including medical information storage, distribution, as well as administration. Given the advantages of cloud computing, several medical companies are exploring implementing such techniques to address various difficulties inside the medical sector. It evolved into an essential component of healthcare delivery. It may help medical companies concentrate on their activities, and medical assistance, including clinical management. This provides a safer approach for sharing confidential material wit

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Guo, Yihong, Jinxin Zuo, Ziyu Guo, Jiahao Qi, and Yueming Lu. "Data Sharing Privacy Metrics Model Based on Information Entropy and Group Privacy Preference." Cryptography 7, no. 1 (2023): 11. http://dx.doi.org/10.3390/cryptography7010011.

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With the development of the mobile internet, service providers obtain data and resources through a large number of terminal user devices. They use private data for business empowerment, which improves the user experience while causing users’ privacy disclosure. Current research ignores the impact of disclosing user non-sensitive attributes under a single scenario of data sharing and lacks consideration of users’ privacy preferences. This paper constructs a data-sharing privacy metrics model based on information entropy and group privacy preferences. Use information theory to model the correlat

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Pasupuleti, Murali Krishna. "Privacy-Preserving Data Sharing Using Differential Privacy in Healthcare." International Journal of Academic and Industrial Research Innovations(IJAIRI) 05, no. 06 (2025): 386–98. https://doi.org/10.62311/nesx/rphcrcscrcp2.

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Abstract: This study evaluates the effectiveness of differential privacy (DP) techniques for privacy-preserving data sharing in healthcare environments. Healthcare data is highly sensitive, making data sharing both a valuable and risky endeavor. Traditional anonymization techniques fail to provide sufficient guarantees against re-identification attacks, particularly in high-dimensional datasets. Differential privacy offers mathematically rigorous privacy guarantees while enabling data utility. Using real-world healthcare datasets, the proposed approach evaluates the trade-off between privacy b

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Sánchez, David, and Alexandre Viejo. "Personalized privacy in open data sharing scenarios." Online Information Review 41, no. 3 (2017): 298–310. http://dx.doi.org/10.1108/oir-01-2016-0011.

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Purpose The purpose of this paper is to propose a privacy-preserving paradigm for open data sharing based on the following foundations: subjects have unique privacy requirements; personal data are usually published incrementally in different sources; and privacy has a time-dependent element. Design/methodology/approach This study first discusses the privacy threats related to open data sharing. Next, these threats are tackled by proposing a new privacy-preserving paradigm. The main challenges related to the enforcement of the paradigm are discussed, and some suitable solutions are identified.

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Chen, Yanjun, Ge Zhang, Chengkun Liu, and Chunjiang Lu. "Privacy-Preserving Modeling of Trajectory Data: Secure Sharing Solutions for Trajectory Data Based on Granular Computing." Mathematics 12, no. 23 (2024): 3681. http://dx.doi.org/10.3390/math12233681.

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Trajectory data are embedded within driving paths, GPS positioning systems, and mobile signaling information. A vast amount of trajectory data play a crucial role in the development of smart cities. However, these trajectory data contain a significant amount of sensitive user information, which poses a substantial threat to personal privacy. In this work, we have constructed an internal secure information granule model based on differential privacy to ensure the secure sharing and analysis of trajectory data. This model deeply integrates granular computing with differential privacy, addressing

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Feng, Tao, Xusheng Wang, Chunyan Liu, and Junli Fang. "Secure Data Collaborative Computing Scheme Based on Blockchain." Security and Communication Networks 2021 (January 13, 2021): 1–9. http://dx.doi.org/10.1155/2021/6630291.

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With the rapid development of information technology, different organizations cooperate with each other to share data information and make full use of data value. Not only should the integrity and privacy of data be guaranteed but also the collaborative computing should be carried out on the basis of data sharing. In this paper, in order to achieve the fairness of data security sharing and collaborative computing, a security data collaborative computing scheme based on blockchain is proposed. A data storage query model based on Bloom filter is designed to improve the efficiency of data query s

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Chen, Yuling, Jinyi Guo, Changlou Li, and Wei Ren. "FaDe: A Blockchain-Based Fair Data Exchange Scheme for Big Data Sharing." Future Internet 11, no. 11 (2019): 225. http://dx.doi.org/10.3390/fi11110225.

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In the big data era, data are envisioned as critical resources with various values, e.g., business intelligence, management efficiency, and financial evaluations. Data sharing is always mandatory for value exchanges and profit promotion. Currently, certain big data markets have been created for facilitating data dissemination and coordinating data transaction, but we have to assume that such centralized management of data sharing must be trustworthy for data privacy and sharing fairness, which very likely imposes limitations such as joining admission, sharing efficiency, and extra costly commi

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Zheng, Bao-Kun, Lie-Huang Zhu, Meng Shen, et al. "Scalable and Privacy-Preserving Data Sharing Based on Blockchain." Journal of Computer Science and Technology 33, no. 3 (2018): 557–67. http://dx.doi.org/10.1007/s11390-018-1840-5.

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Su, Yilun. "Study on Blockchain-based data sharing security." BCP Business & Management 38 (March 2, 2023): 659–65. http://dx.doi.org/10.54691/bcpbm.v38i.3755.

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Within the context of the big data age, data sharing is gradually rising with the embodiment of data value. Data value can increase through sharing, but there are security problems during the period of data sharing such as centralized deployment, malicious theft, and tampering, which greatly affect the security of data. Aiming at the common privacy leakage problem during data sharing, this research builds a data sharing platform on the chain based on blockchain technology, and combines the function encryption technology and zero-knowledge proof technology to realize the sharing of verifiable c

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Feng, Tao, Pu Yang, Chunyan Liu, Junli Fang, and Rong Ma. "Blockchain Data Privacy Protection and Sharing Scheme Based on Zero-Knowledge Proof." Wireless Communications and Mobile Computing 2022 (February 23, 2022): 1–11. http://dx.doi.org/10.1155/2022/1040662.

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The data generated in the Industrial Internet of Things (IIoT) has important research value. In the process of data sharing, data privacy, security, and data availability are important issues that cannot be ignored. This paper proposes a blockchain privacy protection scheme based on zero-knowledge proof to realize the secure sharing of data among data owners, cloud service providers, and semitrusted cloud servers. First, the method of combining zero-knowledge proof and smart contract is used to verify the availability of data between the data owner and the cloud service provider under the prem

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Ma, Tinghuai, Yuming Su, Huan Rong, Yurong Qian, and Najla Al-Nabhan. "Rule Fusion of Privacy Protection Strategies for Co-Ownership Data Sharing." Mathematics 10, no. 6 (2022): 969. http://dx.doi.org/10.3390/math10060969.

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With the rapid development of social networks, personal privacy leakage has become more and more serious. A social network is a shared platform. Resources in a social network may be shared by multiple owners. In order to prevent privacy leakage, each owner assigns a corresponding privacy protection strategy. For the same shared contents, integrating the privacy protection strategies of all owners is the key problem for sharing. This paper proposes a rule fusion method of privacy protection for the co-ownership of data shared in social networks. First, the content of the protection is defined a

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Villanueva, Angela G., Robert Cook-Deegan, Jill O. Robinson, Amy L. McGuire, and Mary A. Majumder. "Genomic Data-Sharing Practices." Journal of Law, Medicine & Ethics 47, no. 1 (2019): 31–40. http://dx.doi.org/10.1177/1073110519840482.

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Making data broadly accessible is essential to creating a medical information commons (MIC). Transparency about data-sharing practices can cultivate trust among prospective and existing MIC participants. We present an analysis of 34 initiatives sharing DNA-derived data based on public information. We describe data-sharing practices captured, including practices related to consent, privacy and security, data access, oversight, and participant engagement. Our results reveal that data-sharing initiatives have some distance to go in achieving transparency.

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Usiabulu, Ehizokhale Jude, Abel Onolunosen Abhadionmhen, and Husseni Iduku. "ML-Powered Privacy Preservation in Biomedical Data Sharing." African Journal of Medicine, Surgery and Public Health Research 2, no. 3 (2025): 389–407. https://doi.org/10.58578/ajmsphr.v2i3.6143.

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The sharing of biomedical data is essential for accelerating healthcare research, fostering medical innovation, and improving patient outcomes. Such data encompasses a wide range of sensitive information, including electronic health records, genomic sequences, and clinical trial results. Despite its value, biomedical data sharing poses significant privacy risks, such as patient re-identification, unauthorized access, and regulatory non-compliance. These concerns necessitate advanced techniques that balance the need for data utility with stringent privacy protection. Machine learning (ML) has e

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Zhou, Haojie, Hongmin Gao, Zhaofeng Ma, and Guanhui Lai. "Blockchain-Based Trusted Data Management with Privacy Preservation for Secure IoT Systems." Sensors 25, no. 14 (2025): 4344. https://doi.org/10.3390/s25144344.

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With the explosive growth of the Internet of Things (IoT), the traditional single data sharing scheme has difficulty satisfying the data sharing needs of both same-domain and cross-domain IoT devices. In order to realize efficient data sharing of IoT devices in the same domain with data privacy protection and efficient collaboration between IoT devices in different domains, this paper proposes a trusted data sharing scheme in IoT systems based on multi-channel blockchain. The scheme adopts a multi-channel mechanism to isolate the ledger data between IoT devices of different domains; IoT device

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Xu, Lu, Mengchen Lin, Yong Feng, and Yani Sun. "BPDST: Blockchain-Based Privacy-Preserving Data Sharing on Thin Client for Electronic Medical Records." Journal of Computing and Information Technology 29, no. 4 (2022): 235–50. http://dx.doi.org/10.20532/cit.2021.1005412.

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Sharing medical data can improve the quality of medical services and reduce costs. However, the current Electronic Medical Records (EMRs) are scattered and easily tampered with, which is not conducive to the sharing of EMRs and is not compatible with thin clients. Fortunately, blockchain technology is tamper-proof, decentralized, auditable, and meets the above requirements. To solve these problems, we first propose Blockchain-Based Privacy-Preserving Data Sharing on Thin-Client for Electronic Medical Records (BPDST) approach that combines the k-anonymity and cloud storage, which thin clients c

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Zhang, Jingchi, and Anwitaman Datta. "Blockchain-enabled data governance for privacy-preserved sharing of confidential data." PeerJ Computer Science 10 (December 20, 2024): e2581. https://doi.org/10.7717/peerj-cs.2581.

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In traditional cloud storage systems, users benefit from the convenience of data accessibility but face significant risks related to security. Ciphertext-policy attribute-based encryption (CP-ABE) schemes are employed to achieve fine-grained access control in cloud services to ensure confidentiality while maintaining data-sharing capabilities. However, existing approaches are impaired by two critical issues: illegal authorization and privacy leakage. Despite extensive discussions in the literature on interoperability, performance, scalability, and stability, the security of ABE-based cloud sto

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21

Niu, Yu, Ji-Jiang Yang, and Qing Wang. "Framework Design and Case Study for Privacy-Preserving Medical Data Publishing." International Journal of E-Health and Medical Communications 4, no. 4 (2013): 48–65. http://dx.doi.org/10.4018/ijehmc.2013100104.

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With the pervasive using of Electronic Medical Records (EMR) and telemedicine technologies, more and more digital healthcare data are accumulated from multiple sources. As healthcare data is valuable for both commercial and scientific research, the demand of sharing healthcare data has been growing rapidly. Nevertheless, health care data normally contains a large amount of personal information, and sharing them directly would bring huge threaten to the patient privacy. This paper proposes a privacy preserving framework for medical data sharing with the view of practical application. The framew

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Barhamgi, Mahmoud, Djamal Benslimane, Chirine Ghedira, and Brahim Medjahed. "An SOA-Based Architecture to Share Medical Data with Privacy Preservation." International Journal of Organizational and Collective Intelligence 2, no. 3 (2011): 11–26. http://dx.doi.org/10.4018/ijoci.2011070102.

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Recent years have witnessed a growing interest in using Web services as a reliable means for medical data sharing inside and across healthcare organizations. In such service-based data sharing environments, Web service composition emerged as a viable approach to query data scattered across independent locations. Patient data privacy preservation is an important aspect that must be considered when composing medical Web services. In this paper, the authors show how data privacy can be preserved when composing and executing Web services. Privacy constraints are expressed in the form of RDF querie

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Zhou, Wei, De Zhang, Guangjie Han, Wenyin Zhu, and Xupeng Wang. "A Blockchain-Based Privacy-Preserving and Fair Data Transaction Model in IoT." Applied Sciences 13, no. 22 (2023): 12389. http://dx.doi.org/10.3390/app132212389.

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The rapid development of the Internet of Things (IoT) has resulted in vast amounts of widely distributed data. Sharing these data can spur innovative advancements and enhance service quality. However, conventional data-sharing methods often involve third-party intermediaries, posing risks of single-point failures and privacy leaks. Moreover, these traditional sharing methods lack a secure transaction model to compensate for data sharing, which makes ensuring fair payment between data consumers and providers challenging. Blockchain, as a decentralized, secure, and trustworthy distributed ledger

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Lin, Junyu, Libo Feng, Jinli Wang, et al. "FGDB‐MLPP: A fine‐grained data‐sharing scheme with blockchain based on multi‐level privacy protection." IET Communications 18, no. 4 (2024): 309–21. http://dx.doi.org/10.1049/cmu2.12737.

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AbstractIn the era of 5G, billions of terminal devices achieve global interconnection and intercommunication, which leads to the generation of massive data. However, the existing cloud‐based data‐sharing mechanism faces challenges such as sensitive information leakage and data islands, which makes it difficult to achieve secure sharing across domains. In this paper, the authors propose a fine‐grained data‐sharing scheme based on blockchain and ciphertext policy attribute‐based encryption, and design a verifiable outsourced computation method to reduce the computational pressure of end users. S

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Wu, Hao, Yu Liu, Konglin Zhu, and Lin Zhang. "Data-Sharing System with Attribute-Based Encryption in Blockchain and Privacy Computing." Symmetry 16, no. 11 (2024): 1550. http://dx.doi.org/10.3390/sym16111550.

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With the development of the data-sharing system in recent years, financial management systems and their privacy have sparked great interest. Existing financial data-sharing systems store metadata, which include a hash value and database index on the blockchain, and store high-capacity actual data in the center database. However, current data-sharing systems largely depend on centralized systems, which are susceptible to distributed denial-of-service (DDoS) attacks and present a centralized attack vector. Furthermore, storing data in a local center database has a high risk of information disclo

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Reddy, P. Raja Sekhar, and K. Ravindranath. "CR-IBE based data sharing and revocation in the cloud." Journal of Discrete Mathematical Sciences and Cryptography 27, no. 2 (2024): 453–64. http://dx.doi.org/10.47974/jdmsc-1901.

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Storing information on the cloud lets users access data quickly. Owners send their files to cloud servers to save money and use helpful tools. Keeping shared data online beyond direct control worries more people about privacy and security. Issues with sharing data in the cloud are a major concern. Several methods can protect user privacy and securely share group information. This paper introduces a secure dynamic way for groups to share and take away access to data using identity-based encryption that can change (R-IBE). A new cloud-based method for sharing data with revocable identity-based e

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Park, Young-Hoon, Yejin Kim, and Junho Shim. "Blockchain-Based Privacy-Preserving System for Genomic Data Management Using Local Differential Privacy." Electronics 10, no. 23 (2021): 3019. http://dx.doi.org/10.3390/electronics10233019.

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The advances made in genome technology have resulted in significant amounts of genomic data being generated at an increasing speed. As genomic data contain various privacy-sensitive information, security schemes that protect confidentiality and control access are essential. Many security techniques have been proposed to safeguard healthcare data. However, these techniques are inadequate for genomic data management because of their large size. Additionally, privacy problems due to the sharing of gene data are yet to be addressed. In this study, we propose a secure genomic data management system

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Xiao, Yao, Lei Xu, Zikang Chen, Can Zhang, and Liehuang Zhu. "A Blockchain-Based Data Sharing System with Enhanced Auditability." Mathematics 10, no. 23 (2022): 4494. http://dx.doi.org/10.3390/math10234494.

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Cloud platforms provide a low-cost and convenient way for users to share data. One important issue of cloud-based data sharing systems is how to prevent the sensitive information contained in users’ data from being disclosed. Existing studies often utilize cryptographic primitives, such as attribute-based encryption and proxy re-encryption, to protect data privacy. These approaches generally rely on a centralized server which may cause a single point of failure problem. Blockchain is known for its ability to solve such a problem. Some blockchain-based approaches have been proposed to realize p

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Jiang, Jiahui, Tingrui Pei, Jiahao Chen, and Zhiwen Hou. "CDAS: A Secure Cross-Domain Data Sharing Scheme Based on Blockchain." Information 16, no. 5 (2025): 394. https://doi.org/10.3390/info16050394.

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In the current context of the wide application of Internet of Things (IoT) technology, cross-domain data sharing based on industrial IoT (IIoT) has become the key to maximizing data value, but it also faces many challenges. In response to the security and privacy issues in cross-domain data sharing, we proposed a cross-domain secure data sharing scheme (CDAS) based on multiple blockchains. The scheme first designs the cross-domain blockchain in layers and assists the device in completing the data sharing on the chain through the blockchain layer close to the edge device. In addition, we combin

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Lee, Yeon-Ji, Na-Yeon Shin, and Il-Gu Lee. "Privacy-Preserving Data Sharing via PCA-Based Dimensionality Reduction in Non-IID Environments." Electronics 14, no. 13 (2025): 2711. https://doi.org/10.3390/electronics14132711.

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The proliferation of mobile devices has generated exponential data growth, driving efforts to extract value. However, mobile data often presents non-independent and identically distributed (non-IID) challenges owing to varying device, environmental, and user factors. While data sharing can mitigate non-IID issues, direct raw data transmission poses significant security risks like privacy breaches and man-in-the-middle attacks. This paper proposes a secure data-sharing mechanism using principal component analysis (PCA). Each node independently builds a local PCA model to reduce data dimensional

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R. UshaRani. "Blockchain-Based Secure Data Sharing for IoT Applications." Journal of Information Systems Engineering and Management 10, no. 37s (2025): 83–89. https://doi.org/10.52783/jisem.v10i37s.6381.

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The swift expansion of Internet of Things (IoT) applications has brought forth considerable challenges in securing data transmission and safeguarding privacy. Conventional centralized data-sharing methods are vulnerable to single points of failure, unauthorized access, and data manipulation. This paper investigates a blockchain-based strategy for securing data sharing within IoT networks. The decentralized and immutable characteristics of blockchain bolster data integrity, confidentiality, and access control. The proposed framework utilizes smart contracts to automate data sharing and enforce

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Fobia, Aleia Clark, Jessica Holzberg, Casey Eggleston, Jennifer Hunter Childs, Jenny Marlar, and Gerson Morales. "Attitudes towards Data Linkage for Evidence-Based Policymaking." Public Opinion Quarterly 83, S1 (2019): 264–79. http://dx.doi.org/10.1093/poq/nfz008.

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Abstract In a recent report, the Commission for Evidence-Based Policymaking advocated for expanded use of data, including data linkage, from federal statistical and regulatory agencies to help guide decision-making and ultimately improve programs and policies. How data sharing and linkage is framed is important, and attitudes about data sharing and linkage are driven by respondents’ privacy beliefs and views towards the government more generally. Using data from the RDD telephone Gallup Daily Tracking Survey, we examine how favorability towards data sharing for the purpose of informed decision

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Yi Lu, Weichao Wang, B. Bhargava, and Dongyan Xu. "Trust-based privacy preservation for peer-to-peer data sharing." IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 36, no. 3 (2006): 498–502. http://dx.doi.org/10.1109/tsmca.2006.871795.

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Piao, Chunhui, Liping Liu, Yajuan Shi, Xuehong Jiang, and Ning Song. "Clustering-based privacy preserving anonymity approach for table data sharing." International Journal of System Assurance Engineering and Management 11, no. 4 (2019): 768–73. http://dx.doi.org/10.1007/s13198-019-00834-5.

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Wang, Jie, Hongtao Li, Feng Guo, Wenyin Zhang, and Yifeng Cui. "D2D Big Data Privacy-Preserving Framework Based on (a, k)-Anonymity Model." Mathematical Problems in Engineering 2019 (August 7, 2019): 1–11. http://dx.doi.org/10.1155/2019/2076542.

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As a novel and promising technology for 5G networks, device-to-device (D2D) communication has garnered a significant amount of research interest because of the advantages of rapid sharing and high accuracy on deliveries as well as its variety of applications and services. Big data technology offers unprecedented opportunities and poses a daunting challenge to D2D communication and sharing, where the data often contain private information concerning users or organizations and thus are at risk of being leaked. Privacy preservation is necessary for D2D services but has not been extensively studie

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V., Geetha, C.K.Gomathy, Sai Charan Kopparapu, and Koushik Mandadi. "A Secure Based Preserving Social Media Data Management System." International Journal of Engineering and Advanced Technology (IJEAT) 10, no. 4 (2021): 210–14. https://doi.org/10.5281/zenodo.5524579.

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Personalized suggestions are important to help users find relevant information. It often depends on huge collection of user data, especially users’ online activity (e.g., liking/commenting/sharing) on social media, thereto user interests. Publishing such user activity makes inference attacks easy on the users, as private data (e.g., contact details) are often easily gathered from the users’ activity data. during this module, we proposed PrivacyRank, an adjustable and always protecting privacy on social media data publishing framework , which protects users against frequent attacks

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Hu, Mingqi, Yanli Ren, and Cien Chen. "Privacy-Preserving Medical Data-Sharing System with Symmetric Encryption Based on Blockchain." Symmetry 15, no. 5 (2023): 1010. http://dx.doi.org/10.3390/sym15051010.

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Nowadays, data between hospitals are usually not interoperable, which brings great inconvenience to medical data sharing and patients’ medical treatment. In addition, patients do not want their medical data to be leaked during the sharing process. Researchers have employed blockchain to build data-sharing systems to address these issues. However, current systems do not restrict the power of participants, nor do they prevent visitors from sharing the obtained data to unauthorized parties. To address these issues, we propose a private data-sharing system with symmetric encryption for the medical

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Jia, Xuedan, Xiangmei Song, and Muhammad Sohail. "Effective Consensus-Based Distributed Auction Scheme for Secure Data Sharing in Internet of Things." Symmetry 14, no. 8 (2022): 1664. http://dx.doi.org/10.3390/sym14081664.

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In a traditional electronic auction, the centralized auctioneer and decentralized bidders are in an asymmetric structure, where the auctioneer has more ability to decide the auction result. This asymmetric auction structure is not fair to the participants and not suitable for data auctions in the Internet of Things (IoT). The blockchain-based auction system, with participant equality and fairness, is typically symmetrical and particularly suitable for IoT data sharing. However, when applied to IoT data sharing in reality, it faces privacy and efficiency problems. In this context, how to guaran

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Liu, Jianwei, Qinyang Miao, Xinmin Fan, Xiaoding Wang, Hui Lin, and Yikun Huang. "Mutual-Supervised Federated Learning and Blockchain-Based IoT Data Sharing." Security and Communication Networks 2022 (October 8, 2022): 1–8. http://dx.doi.org/10.1155/2022/7003426.

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Due to the decentralized, tamper-proof, and auditable properties of blockchain, more and more scholars and researchers are studying the application of blockchain technology in IoT data sharing. Federated learning is an effective way to enable data sharing, but can be compromised by dishonest data owners who may provide malicious models. In addition, dishonest data requesters may also infer private information from model parameters. To solve the above problems, a secure data sharing mechanism based on mutual-supervised federated learning and blockchain, BPCV-FL, is proposed. This mechanism ensu

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Wang, Lianhai, Lingyun Meng, Fengkai Liu, et al. "A User-Centered Medical Data Sharing Scheme for Privacy-Preserving Machine Learning." Security and Communication Networks 2022 (September 30, 2022): 1–16. http://dx.doi.org/10.1155/2022/3670107.

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With the rapid development and application of artificial intelligence technology, medical data play an increasingly important role in the medical field. However, there are privacy protection and data ownership issues in the process of data sharing, which brings difficulties to machine learning and data mining. On the one hand, for fear that they may risk being held accountable by users or even breaking the law due to these issues, healthcare providers are reluctant to share medical data. On the other hand, users are also reluctant to share medical data due to the possibility of privacy disclos

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Khalid, Muhammad Irfan, Mansoor Ahmed, Markus Helfert, and Jungsuk Kim. "Privacy-First Paradigm for Dynamic Consent Management Systems: Empowering Data Subjects through Decentralized Data Controllers and Privacy-Preserving Techniques." Electronics 12, no. 24 (2023): 4973. http://dx.doi.org/10.3390/electronics12244973.

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This paper explicitly focuses on utilizing blockchain technology in dynamic consent management systems with privacy considerations. While blockchain offers improved security, the potential impact on entities’ privacy must be considered. Through a critical investigation of available contributions to the present state of the art of blockchain-based dynamic consent management systems, we highlight the limitations of plaintext storage and the processing of subject data/consent on the blockchain, which can compromise privacy. We stress the significance of keeping encrypted subject data/consent on t

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Bourdoucen, Amel, and Janne Lindqvist. "My Data or Our Data? A Comparative Study of Collaborative Family Apps and Parents' Experiences with Apple's Family Sharing." Proceedings on Privacy Enhancing Technologies 2025, no. 4 (2025): 812–37. https://doi.org/10.56553/popets-2025-0159.

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Collaborative family apps are designed for families to stay connected, look after their kids, and share life events. Despite their well-intended design, collaborative family apps can be invasive, leading to tensions in family relationships and exposure to online risks. We compared frequently downloaded collaborative family and parental control apps in terms of their features, with a focus on Apple's Family Sharing and Google's Family Link. We then conducted a qualitative interview study (N=20) to explore privacy experiences when using Apple's Family Sharing. Our results highlight privacy chall

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Pooja and Neelambika. "Privacy Protection and Intrusion Avoidance for Cloudlet Based Medical Data Sharing." International Journal of Trend in Scientific Research and Development 2, no. 4 (2018): 2529–33. https://doi.org/10.31142/ijtsrd15628.

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With the ubiquity of wearable gadgets, alongside the advancement of clouds and cloudlet innovation, there has been expanding need to give better medical care. The preparing chain of medical information mostly incorporates information accumulation, information stockpiling and information sharing, and so forth. Customary medicinal services system regularly requires the conveyance of medical information to the cloud, which includes clients delicate data and causes correspondence vitality utilization. For all intents and purposes, medical information sharing is a basic and testing issue. Subsequen

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Jiang, Xue Mei, and Da Shen Xue. "Data Sanitization Based on Weaken_Sensitive_Pattern Tree." Advanced Materials Research 756-759 (September 2013): 3167–71. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.3167.

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In data sharing, protecting the user's privacy data is very important. This article is based on data sanitization thought, and studies the protection of sensitive information. Then we proposed data sanitization algorithm (the Dpur algorithm), which is based on the weaken_sensitive_pattern tree. The results show that under the influencing of privacy protection factor, Dpur algorithm is superior to the SWA algorithm. When the shared data is the original data set, Dpur algorithm provides more efficient data sanitization.

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Shetty, Nisha P., Balachandra Muniyal, Nandini Proothi, and Bhavya Gopal. "Collusion-resistant multiparty data sharing in social networks." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 2 (2024): 1996. http://dx.doi.org/10.11591/ijece.v14i2.pp1996-2013.

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The number of users on online social networks (OSNs) has grown tremendously over the past few years, with sites like Facebook amassing over a billion users. With the popularity of OSNs, the increase in privacy risk from the large volume of sensitive and private data is inevitable. While there are many features for access control for an individual user, most OSNs still need concrete mechanisms to preserve the privacy of data shared between multiple users. The proposed method uses metrics such as identity leakage (IL) and strength of interaction (SoI) to fine-tune the scenarios that use privacy

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Shetty, Nisha P., Balachandra Muniyal, Nandini Proothi, and Bhavya Gopal. "Collusion-resistant multiparty data sharing in social networks." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 2 (2024): 1996–2013. https://doi.org/10.11591/ijece.v14i2.pp1996-2013.

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The number of users on online social networks (OSNs) has grown tremendously over the past few years, with sites like Facebook amassing over a billion users. With the popularity of OSNs, the increase in privacy risk from the large volume of sensitive and private data is inevitable. While there are many features for access control for an individual user, most OSNs still need concrete mechanisms to preserve the privacy of data shared between multiple users. The proposed method uses metrics such as identity leakage (IL) and strength of interaction (SoI) to fine-tune the scenarios that use privacy

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Badugu Ranjith Kumar, Et al. "KBD-Share: Key Aggregation, Blockchain, and Differential Privacy based Secured Data Sharing for Multi-User Cloud Computing." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 10 (2023): 1290–301. http://dx.doi.org/10.17762/ijritcc.v11i10.8672.

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In today's era of widespread cloud computing and data sharing, the demand for secure and privacy-preserving techniques to facilitate multi-user data sharing is rapidly increasing. However, traditional approaches struggle to effectively address the twin objectives of ensuring privacy protection while preserving the utility of shared data. This predicament holds immense significance due to the pivotal role data sharing plays in diverse domains and applications. However, it also brings about significant privacy vulnerabilities. Consequently, innovative approaches are imperative to achieve a harmo

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S. Raj, Jennifer. "Secure Data Sharing Platform for Portable Social Networks with Power Saving Operation." September 2021 3, no. 3 (2021): 250–62. http://dx.doi.org/10.36548/jismac.2021.3.006.

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Several subscribing and content sharing services are largely personalized with the growing use of mobile social media technology. The end user privacy in terms of social relationships, interests and identities as well as shared content confidentiality are some of the privacy concerns in such services. The content is provided with fine-grained access control with the help of attribute-based encryption (ABE) in existing work. Decryption of privacy preserving content suffers high consumption of energy and data leakage to unauthorized people is faced when mobile social networks share privacy prese

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Jain, Meenu, and Manisha Jalia. "Blockchain-Based Data Sharing Approach Considering Educational Data." International Journal of Information Security and Privacy 16, no. 1 (2022): 1–20. http://dx.doi.org/10.4018/ijisp.303666.

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The innovation of cloud computing technologies gained huge interest wherein more individuals started to outsource their data to cloud-based servers. However, open networks and untrusted cloud platforms face privacy and security issues while outsourcing data to the cloud. The proposed Blockchain-based data sharing mechanism effectively solves failure issues of the cloud storage system and provides several benefits by maximizing throughput. This framework embeds the Interplanetary File System and blockchain for effective data sharing between cloud owners and the requester. Here, the system compr

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Qin, Mingzhi, and Qingtao Wu. "A Review of Blockchain-Based Research on E-Health Data Sharing." International Journal of Computer Science and Information Technology 3, no. 1 (2024): 37–43. http://dx.doi.org/10.62051/ijcsit.v3n1.06.

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With the development of medical data informatization, the data security, data privacy, and data controllability of electronic medical data with patient's personal privacy have gained social attention. Blockchain technology has decentralized characteristics, and the development of blockchain technology provides an effective solution for the secure sharing of e-medical data. Many scholars have proposed e-medical data security sharing solutions based on blockchain technology, and these solutions have attempted to solve the security problems encountered in sharing traditional e-medical data. By su

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