Algorithm of blockchain data provenance based on ABE by Youliang TIAN, Kedi YANG, Zuan WANG, Tao FENG

“…To solve the problem that the blockchain-based traceability algorithm mainly used homomorphic encryption and zero-knowledge proof for privacy protection,making it difficult to achieve dynamic sharing of traceability information,a blockchain data traceability algorithm based on attribute encryption was proposed.In order to realize the dynamic protection of transaction privacy,the strategy update algorithm applicable to block chain was designed based on the CP-ABE scheme proposed by Waters to achieve dynamic protection of transaction privacy.In order to realize the dynamic update of the visibility about block content,based on the strategy update algorithm,the block structure was designed to achieve the dynamic update about the content visibility of the block.The security and experimental simulation analysis show that the proposed algorithm can realize the dynamic sharing of traceability information while completing the protection transaction privacy.…”
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Decentralized Voltage Prediction in Multi-Area Distribution Systems: A Privacy-Preserving Collaborative Framework by Jianfeng Yan, Beibei Wang, Zhiqiang Wu, Zhengkai Ding

“…However, potential privacy concerns pose significant challenges to data sharing and interarea collaboration. …”
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A decentralized privacy-preserving framework for diabetic retinopathy detection using federated learning and blockchain by Omar Dib

“…Diabetic Retinopathy (DR) detection in distributed telemedicine environments requires secure, scalable, and privacy-preserving solutions. Traditional federated learning (FL) relies on a central server, raising concerns about data privacy and system trust. …”
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Privacy-preserving detection and classification of diabetic retinopathy using federated learning with FedDEO optimization by Dasari Bhulakshmi, Dharmendra Singh Rajput

“…FL enables collaborative learning across multiple decentralized devices while maintaining data privacy. FedDEO optimization enhances the model's performance by fine-tuning hyperparameters in a distributed manner. …”
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Application of the joint clustering algorithm based on Gaussian kernels and differential privacy in lung cancer identification by Hang Yanping, Zheng Haixia, Yang Minmin, Wang Nan, Kong Miaomiao, Zhao Mingming

“…The algorithm enhances cancer detection while ensuring data privacy. Three publicly available lung cancer datasets, along with a dataset from our hospital, are used to test and demonstrate the effectiveness of DPFCM_GK. …”
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A lightweight and efficient raw data collection scheme for IoT systems by Yixuan Huang, Yining Liu, Jingcheng Song, Weizhi Meng

“…However, it also exposes sensitive information, which leads to privacy risks. An approach called N-source anonymity has been used for privacy preservation in raw data collection, but most of the existing schemes do not have a balanced efficiency and robustness. …”
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Enhanced Privacy and Communication Efficiency in Non-IID Federated Learning With Adaptive Quantization and Differential Privacy by Emre Ardic, Yakup Genc

“…We evaluate our approach through extensive experiments on CIFAR10, MNIST, and medical imaging datasets, using non-IID data distributions across varying client counts, bit-length schedulers, and privacy budgets. …”
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Enhancing uploads of health data in the electronic health record—The role of framing and length of privacy information: A survey study in Germany by Niklas von Kalckreuth, Markus A Feufel

“…Background The German electronic health record (EHR) aims to enhance patient care and reduce costs, but users often worry about data security. In this article, we propose and test communication strategies to mitigate privacy concerns and increase EHR uploads. …”
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Exploring the General Data Protection Regulation (GDPR) compliance in cloud services: insights from Swedish public organizations on privacy compliance by Awatef Issaoui, Jenny Örtensjö, M. Sirajul Islam

“…The collected data were analyzed and classified using the seven privacy threat categories outlined in the LINDDUN framework. …”
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Googling Patients by Emily Beer

“…It can be difficult to determine which health data is truly private or confidential. In our collective effort to decide how to categorize and use data, it is important not to muddy the waters unnecessarily by applying concepts of privacy and confidentiality to data that definitely does not meet those criteria and simply is not private. …”
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Social Aspects of Democratic Safeguards in Privacy Rights: A Qualitative Study of the European Union and China by Polonca Kovač, Grega Rudolf

“… Purpose: The primary objective of the present research is to identify the basic tools and restrictions concerning the protection of privacy and personal data in the EU and China as two fundamentally different cultural systems. …”
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Research and prospect of reversible data hiding method with contrast enhancement by Yang YANG, Wei-ming ZHANG, ong-dong HOUD, Hui WANG, Neng-hai YU

“…Reversible data hiding methods can recover the cover image losslessly after extracting the secret message from the marked image.Such technology can be used in the certification or the label of military,justice and medical images,which are sensitive and slight modification are not allowed.Especially for the medical images,RDH tech-nology can be used in protecting the privacy of the patient.A series of RDH methods with contrast enhancement ef-fect were introduced and classified into pixel-based histogram methods and prediction-error-based histogram meth-ods according to the type of carrier in RDH scheme.The main purpose of such algorithms was to improve the sub-jective visual quality of marked images and to embed secret data into cover image reversibly meanwhile.These se-ries of algorithms were suitable for the research of privacy protection of medical image.Finally,future development in this direction is prospected through analyzing the advantages and disadvantages of the existing work.…”
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Optimising data sharing whilst protecting participant privacy: a data note describing processed data from a qualitative study of healthcare professionals’ experiences of caring for... by Hannah A. Long, Peter Branney, David P. French, Joanna M. Brooks

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Efficient Access Control for Video Anomaly Detection Using ABE-Based User-Level Revocation with Ciphertext and Index Updates by Lu Jiang, Jielu Yan, Weizhi Xian, Xuekai Wei, Xiaofeng Liao

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Sentimental analysis based federated learning privacy detection in fake web recommendations using blockchain model by Jitendra Kumar Samriya, Amit Kumar, Ashok Bhansali, Meena Malik, Varsha Arya, Wadee Alhalabi, Bassma Saleh Alsulami, Brij B. Gupta

“…This work offers an experimental analysis of diverse sentiment data-driven fake recommendation datasets, evaluating performance using accuracy, precision, recall, and F-measure metrics. …”
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Research on algorithms of data encryption scheme that supports homomorphic arithmetical operations by ANGPan Y, UIXiao-lin G, AOJing Y, INJian-cai L, IANFeng T, HANGXue-jun Z

“…An efficient homomorphic encryption scheme called CESIL was proposed to meet the requirements of operating on encrypted data when protecting users' privacy in computing services.CESIL included key generation algorithm,encryption algorithm,decryption algorithm and calculation algorithm.In CESIL,a polynomial coefficient vector ring was established by defining addition and multiplication using polynomial ring; by using ideal lattice,the vector ring was partitioned into many residue classes to produce a quotient ring and its representative set; the plaintext was encrypted by mapping it to a representative and replacing the representative with another element in the same residue class.The features of operations in quotient ring ensured CESIL operate on encrypted data.Furthermore,the fast Fourier transform (FFT) algorithm was used to increase the efficiency and decrease the length of key.Theoretical analysis and experimental results show that CESIL is semantically secure,and can do addition and multiplication operations on encrypted data homomorphically in a specific scope.Comparing to some existing homomorphic encryption schemes,the CESIL runs efficiently,and has shorter length in key and ciphertext.Thus,the CESIL fits the practical applications better.…”
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Building Equi-Width Histograms on Homomorphically Encrypted Data by Dragoș Lazea, Anca Hangan, Tudor Cioara

“…Histograms are widely used for summarizing data distributions, detecting anomalies, and improving machine learning models’ accuracy. …”
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Privacy-Preserving Process Mining: A Blockchain-Based Privacy-Aware Reversible Shared Image Approach by Xianwen Fang, Mengyao Li

“…Deeper integration of cross-organizational business process sharing and process mining has advanced the Industrial Internet. Privacy breaches and data security risks limit its use. …”
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Does data privacy influence digital marketing? The mediating role of AI-driven trust: An empirical study of Zain Telecom company in Jordan by Nidal Al Said

“…The PLS-SEM technique was used in this research to analyze data privacy, digital marketing effectiveness, and AI-driven trust constructs. …”
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Data Obfuscation Through Latent Space Projection for Privacy-Preserving AI Governance: Case Studies in Medical Diagnosis and Finance Fraud Detection by Mahesh Vaijainthymala Krishnamoorthy

“… Abstract BackgroundThe increasing integration of artificial intelligence (AI) systems into critical societal sectors has created an urgent demand for robust privacy-preserving methods. Traditional approaches such as differential privacy and homomorphic encryption often struggle to maintain an effective balance between protecting sensitive information and preserving data utility for AI applications. …”
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