Unique Method for Prognosis of Risk of Depressive Episodes Using Novel Measures to Model Uncertainty Under Data Privacy by Barbara Pękala, Dawid Kosior, Wojciech Rząsa, Katarzyna Garwol, Janusz Czuma

“…The computer support system designed for that purpose combines data privacy protection from various sources and uncertainty modeling, especially for incomplete data. …”
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A privacy-preserved horizontal federated learning for malignant glioma tumour detection using distributed data-silos. by Shagun Sharma, Kalpna Guleria, Ayush Dogra, Deepali Gupta, Sapna Juneja, Swati Kumari, Ali Nauman

“…Additionally, it also has patient data-privacy concerns leading to anonymous information generalization, regulatory compliance issues, and data leakage challenges. …”
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A Differential Privacy Framework with Adjustable Efficiency–Utility Trade-Offs for Data Collection by Jongwook Kim, Sae-Hong Cho

“…The widespread use of mobile devices has led to the continuous collection of vast amounts of user-generated data, supporting data-driven decisions across a variety of fields. …”
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Secondary use under the European Health Data Space: setting the scene and towards a research agenda on privacy-enhancing technologies by Sarah van Drumpt, Kartik Chawla, Tom Barbereau, Dayana Spagnuelo, Linda van de Burgwal

Subjects: “…European Health Data Space…”
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The Dual Nature of Trust in Participatory Sciences: An Investigation into Data Quality and Household Privacy Preferences by Danielle Lin Hunter, Valerie Johnson, Caren Cooper

“…In Crowd the Tap, we engaged participants through facilitator organizations including high schools, faith communities, universities, and a corporate volunteer program. We used Kruskal Wallis tests and chi-square tests with Bonferroni post hoc tests to assess how data quality and privacy preferences differed across facilitator groups and amongst those who participated in the project independently (unfacilitated). …”
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Technology Policy Recommendations Using Artificial Intelligence by Ashita Anuga, Minh Nguyen, Dominick Perini, Andrei Svetovidov, Amanda Tolman, Qasim Wani, Feras A. Batarseh

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A Comprehensive Study of Traditional and Deep-learning Schemes for Privacy and Data Security in the Cloud by mohammed sheet, Melad saeed

“…However, it faces great difficulties in ensuring data confidentiality and privacy. People hesitate to use it due to the risk of innumerable attacks and security breaches. …”
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Soulbound Tokens: Enabler for Privacy-Aware and Decentralized Authentication Mechanism in Medical Data Storage by Biagio Boi, Franco Cirillo, Marco De Santis, Christian Esposito

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Efficient privacy-preserving image retrieval scheme over outsourced data with multi-user by Xiangyu WANG, Jianfeng MA, Yinbin MIAO

“…The traditional privacy-preserving image retrieval schemes not only bring large computational and communication overhead,but also cannot protect the image and query privacy in multi-user scenarios.To solve above problems,an efficient privacy-preserving content-based image retrieval scheme was proposed in multi-user scenarios.The scheme used Euclidean distance comparison technique to rank the pictures according to similarity of picture feature vectors and return top-k returned.Meanwhile,the efficient key conversion protocol designed in proposed image retrieval scheme allowed each search user to generate queries based on his own private key so that he can retrieval encrypted images generated by different data owners.Strict security analysis shows that the user privacy and cloud data security can be well protected during the image retrieval process,and the performance analysis using real-world dataset shows that the proposed image retrieval scheme is efficient and feasible in practical applications.…”
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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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Efficient and privacy-preserving certificateless data aggregation in Internet of things–enabled smart grid by Aijing Sun, Axin Wu, Xiaokun Zheng, Fangyuan Ren

“…If the user’s electricity consumption is transmitted in plaintext, the data may be used by some illegal users. At the same time, malicious users may send false data such that the control center makes a wrong power resource scheduling. …”
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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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An explainable federated blockchain framework with privacy-preserving AI optimization for securing healthcare data by Tanisha Bhardwaj, K. Sumangali

“…Abstract With the rapid growth of healthcare data and the need for secure, interpretable, and decentralized machine learning systems, Federated Learning (FL) has emerged as a promising solution. …”
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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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Shuffled differential privacy protection method for K-Modes clustering data collection and publication by Weijin JIANG, Yilin CHEN, Yuqing HAN, Yuting WU, Wei ZHOU, Haijuan WANG

“…Aiming at the current problem of insufficient security in clustering data collection and publication, in order to protect user privacy and improve data quality in clustering data, a privacy protection method for K-Modes clustering data collection and publication was proposed without trusted third parties based on the shuffled differential privacy model.K-Modes clustering data collection algorithm was used to sample the user data and add noise, and then the initial order of the sampled data was disturbed by filling in the value domain random arrangement publishing algorithm.The malicious attacker couldn’t identify the target user according to the relationship between the user and the data, and then to reduce the interference of noise as much as possible a new centroid was calculated by cyclic iteration to complete the clustering.Finally, the privacy, feasibility and complexity of the above three methods were analyzed from the theoretical level, and the accuracy and entropy of the three real data sets were compared with the authoritative similar algorithms KM, DPLM and LDPKM in recent years to verify the effectiveness of the proposed model.The experimental results show that the privacy protection and data quality of the proposed method are superior to the current similar algorithms.…”
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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

“…This method can ensure privacy and protect data while also enhancing the effectiveness and performance of big data analytics. …”
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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

“…Security is always a hot topic in wireless sensor networks (WSNs). Privacy-preserving data aggregation has emerged as an important concern in designing data aggregation algorithm. …”
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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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