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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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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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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Human Behavior Analysis Using Radar Data: A Survey by Patrycja Miazek, Alicja Zmudzinska, Pawel karczmarek, Adam Kiersztyn

“…In this study, we focus not only on the analysis of human behavior using radar but also on video observations. We review methods of human activity recognition using LiDAR. …”
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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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Human Daily Indoor Action (HDIA) Dataset: Privacy-Preserving Human Action Recognition Using Infrared Camera and Wearable Armband Sensors by Jongbum Park, Kyoung Ok Yang, Sunme Park, Jun Won Choi

“…The use of IR sensors enhances privacy, making the dataset ethically suitable for long-term monitoring. …”
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Cultural Differences in the Use of Augmented Reality Smart Glasses (ARSGs) Between the U.S. and South Korea: Privacy Concerns and the Technology Acceptance Model by Se Jung Kim, Yoon Esther Lee, T. Makana Chock

“…Korean respondents had significantly greater privacy concerns about using ARSGs than U.S. respondents. …”
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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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A Novel Polynomial Activation for Audio Classification Using Homomorphic Encryption by Linh Nguyen, Quoc Bao Phan, Lan Zhang, Tuy Tan Nguyen

“…Audio data often contains sensitive information, raising privacy concerns when using artificial intelligence on cloud platforms. …”
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Anomaly detection in encrypted network traffic using self-supervised learning by Sadaf Sattar, Shumaila Khan, Muhammad Ismail Khan, Ainur Akhmediyarova, Orken Mamyrbayev, Dinara Kassymova, Dina Oralbekova, Janna Alimkulova

“…In this paper, we describe ET-SSL, a new approach for encrypted data anomaly detection which uses self-supervised contrastive learning to identify informative representations in flow level, statistical features like packet length; inter arrival time; flow duration and protocol metadata to Detect anomalies in encrypted network traffic without the need for labelled datasets or payload analysis. …”
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Optimizing Customer Data Security in Water Meter Data Management Based on RESTful API and Data Encryption Using AES-256 Algorithm by Syahrul Adrianto, Bambang Agus Herlambang, Ramadhan Renaldy

“…To increase the security of customer data, a cryptographic algorithm is used, namely the Advanced Encryption Standard (AES) algorithm with a 256-bit key length to secure data that is considered sensitive and contains high privacy. …”
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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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UniFL: Accelerating Federated Learning Using Heterogeneous Hardware Under a Unified Framework by Biyao Che, Zixiao Wang, Ying Chen, Liang Guo, Yuan Liu, Yuan Tian, Jizhuang Zhao

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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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EXPLORING USER PERSPECTIVES ON THE APPLICATIONS OF ARTIFICIAL INTELLIGENCE IN FINANCIAL TECHNOLOGY by Sadhana Tiwari, Mohammad Asif, Amar Johri, Mohammad Wasiq, Mohd Imran

“…Structural equation modeling was employed to study the relationships between the adoption of fintech AI and its predictors, namely Perceived Usefulness, Perceived Privacy and Security, Perceived Ease of Use, and Satisfaction of Fintech AI. …”
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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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The digital fingerprint of learner behavior: Empirical evidence for individuality in learning using deep learning by Asaf Salman, Giora Alexandron

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A novel federated learning approach for IoT botnet intrusion detection using SHAP-based knowledge distillation by Md. Alamgir Hossain, Sadman Saif, Md. Saiful Islam

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