A controllable privacy data transmission mechanism for Internet of things system based on blockchain by ZiXiang Nie, YuanZhenTai Long, SenLin Zhang, YueMing Lu

“…With the in-depth integration of traditional industries and information technology in Internet of things, wireless sensor networks are used more frequently to transmit the data generated from various application scenarios. …”
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Preserving Big Data Privacy in Cloud Environments Based on Homomorphic Encryption and Distributed Clustering by Shatha A. Baker

“…A partial homomorphic encryption system is used to encrypt data created by many sources or users and processed in the cloud without decrypting it, hence protecting data from attackers. …”
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South African Electoral Commission’s mobile app for voters: Data privacy and security dimensions by Nawal Omar, Scott Timcke

“…The analysis revealed several security and privacy concerns, including inadequately secured API keys, the potential for unauthorised access, and the potential for data breaches. …”
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An explainable federated blockchain framework with privacy-preserving AI optimization for securing healthcare data by Tanisha Bhardwaj, K. Sumangali

“…The Entropy Deep Belief Network (EDBN) is used as the classifier to enhance classification accuracy and detect attacks. …”
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DP-FedCMRS: Privacy-Preserving Federated Learning Algorithm to Solve Heterogeneous Data by Yang Zhang, Shigong Long, Guangyuan Liu, Junming Zhang

“…In federated learning, non-independently and non-identically distributed heterogeneous data on the clients can limit both the convergence speed and model utility of federated learning, and gradients can be used to infer original data, posing a threat to user privacy. …”
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Decoding privacy concerns: the role of perceived risk and benefits in personal health data disclosure by Havva Nur Atalay, Şebnem Yücel

“…Results The analysis revealed a significant negative relationship between individuals’ personal health data disclosure behaviour and their privacy concerns. …”
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A synchronous compression and encryption method for massive electricity consumption data privacy preserving by Ruifeng Zhao, Jiangang Lu, Zhiwen Yu, Kaiwen Zeng

“…Our proposed algorithm uses a ternary Logistic-Tent chaotic system for generating a chaotic measurement matrix, allowing simultaneous data compression and encryption of user-side voltage and current data. …”
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Privacy-Preserving Keyword Search With Access Control for Secret Sharing-Based Data Outsourcing by Ahmad Akmal Aminuddin Mohd Kamal, Masamune Okada, Masaya Fujisawa

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Privacy-preserving federated learning for collaborative medical data mining in multi-institutional settings by Rahul Haripriya, Nilay Khare, Manish Pandey

“…Abstract Ensuring data privacy in medical image classification is a critical challenge in healthcare, especially with the increasing reliance on AI-driven diagnostics. …”
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Precision-Enhanced and Encryption-Mixed Privacy-Preserving Data Aggregation in Wireless Sensor Networks by Geng Yang, Sen Li, Xiaolong Xu, Hua Dai, Zhen Yang

“…Based on the Slice-Mix-AggRegaTe (SMART) scheme, it optimizes data slicing by using small data packet, node classifying, and positive and negative data slicing techniques. …”
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Time-based and privacy protection revocable and traceable data sharing scheme in cloud computing by Jiawei ZHANG, Jianfeng MA, Zhuo MA, Teng LI

“…General ciphertext-policy attribute-based encryption (CP-ABE) provides fine-grained access control for data sharing in cloud computing, but its plaintext formed access policy may cause leakage of private and sensitive data.And revoking a malicious user by accurately tracing the identity according to a leaked decryption key is a huge challenge.Moreover, most of existing revocable schemes incur long user revocation list and low efficiency.To solve these problems, a time-based and privacy preserving revocable and traceable data sharing scheme was proposed based on CP-ABE to support expressive monotonic and partial hidden access policy, large attribute universe by conceal the attribute values in access policy.Time-limited data access control using hierarchical identity-based encryption was achieved to set key valid period for users.Moreover, with the approaches of white-box tracing and binary tree, efficient user tracing and direct revocation with shorter revocation list was realized together with high efficiency via online/offline and verifiable outsourced decryption techniques.Furthermore, the scheme was secure under decisional q-BDHE assumption.Theoretical analysis and extensive experiments demonstrate its advantageous performance in computational and storage cost.…”
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A blockchain-based verifiable CP-ABE scheme for medical data privacy protection by Leilei Zhao, Guofang Dong, Hao Yuan

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Advancing Data Privacy in Cloud Storage: A Novel Multi-Layer Encoding Framework by Kamta Nath Mishra, Rajesh Kumar Lal, Paras Nath Barwal, Alok Mishra

“…Data privacy is a crucial concern for individuals using cloud storage services, and cloud service providers are increasingly focused on meeting this demand. …”
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Privacy Risk Assessment of Medical Big Data Based on Information Entropy and FCM Algorithm by Xiaoliang Zhang, Tianwei Guo

“…However, the high sensitivity and privacy of medical data also bring serious security challenges. …”
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A Blockchain-Based Secure Data Transaction and Privacy Preservation Scheme in IoT System by Jing Wu, Zeteng Bian, Hongmin Gao, Yuzhe Wang

“…With the explosive growth of Internet of Things (IoT) devices, massive amounts of heterogeneous data are continuously generated. However, IoT data transactions and sharing face multiple challenges such as limited device resources, untrustworthy network environment, highly sensitive user privacy, and serious data silos. …”
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Multi-party summation query method based on differential privacy by Xianmang HE

“…Differential privacy is considered to be a very reliable protection mechanism because it does not require the a prior knowledge for the attacker.However,differential privacy is rarely used in a multi-party environment.In view of this,the differential privacy is applied to the data summation query in multi-party environment.This method was described in detail and proved the security of the method.…”
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Efficient and Privacy-Preserving Decision Tree Inference via Homomorphic Matrix Multiplication and Leaf Node Pruning by Satoshi Fukui, Lihua Wang, Seiichi Ozawa

“…Cloud computing is widely used by organizations and individuals to outsource computation and data storage. …”
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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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A differentially-private mechanism for multi-level data publishing by Wen-jing ZHANG, Hui LI

“…Privacy preserving technology had addressed the problem of privacy leakage during data publishing proc-ess,however,current data publishing technologies mostly focused on publishing privacy preserving data with single level,without considering some scenarios of multi-level users.Therefore,a differentially-private mechanism for multi-level data publishing was proposed.The proposed mechanism employed the Laplace mechanism with different privacy budgets to output results with different privacy protection levels.After the user’s level was determined ac-cording to the charge or privilege of that specific user,the goal that a user with high(low) level can only use the out-put result with low(high) privacy protection level which had low(high) error rate could be achieved.Finally,the evaluation results and security analysis show that our proposed framework can not only prevent from background knowledge attack,but also achieve multi-level data publishing with different error rates effectively .…”
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