Calibrated optional randomized response techniques for efficient and robust estimation of quantitative sensitive variables by Ahmed Audu, Mojeed Abiodun Yunusa, Maggie Aphane, Maria Lekganyane

“…Numerical applications using both real and simulated data supported the theoretical findings, demonstrating that the C-ORRT models exhibited lower biases, reduced variances, higher relative efficiency, enhanced privacy levels, and a better combined metric of variance and privacy. …”
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LightLSB: a lightweight secure transmission mechanism for large-scale biometric images in computing limited environment by ZHANG Denghui, SHEN Shengshang, YAO Jiefeng, LI Mohan, LI Aiping

“…The widespread use of biometric recognition has intensified social concerns about personal privacy disclosure. …”
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Ethical and regulatory challenges in machine learning-based healthcare systems: A review of implementation barriers and future directions by Shehu Mohammed, Neha Malhotra

“…Key issues concern patient data privacy, algorithmic bias, absence of transparency, and ambiguous legal liability. …”
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Establishing and evaluating trustworthy AI: overview and research challenges by Dominik Kowald, Dominik Kowald, Sebastian Scher, Sebastian Scher, Viktoria Pammer-Schindler, Viktoria Pammer-Schindler, Peter Müllner, Kerstin Waxnegger, Lea Demelius, Lea Demelius, Angela Fessl, Angela Fessl, Maximilian Toller, Inti Gabriel Mendoza Estrada, Ilija Šimić, Vedran Sabol, Andreas Trügler, Andreas Trügler, Andreas Trügler, Eduardo Veas, Eduardo Veas, Roman Kern, Roman Kern, Tomislav Nad, Simone Kopeinik

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Synthetic data production for biomedical research by Yun Gyeong Lee, Mi-Sook Kwak, Jeong Eun Kim, Min Sun Kim, Dong Un No, Hee Youl Chai

“…Synthetic data, generated using advanced artificial intelligence (AI) techniques, replicates the statistical properties of real-world datasets while excluding identifiable information. …”
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HoRNS-CNN model: an energy-efficient fully homomorphic residue number system convolutional neural network model for privacy-preserving classification of dyslexia neural-biomarkers by Opeyemi Lateef Usman, Ravie Chandren Muniyandi, Khairuddin Omar, Mazlyfarina Mohamad, Ayoade Akeem Owoade, Morufat Adebola Kareem

“…Although, fully homomorphic encryption (FHE)-based methods have been proposed to maintain data confidentiality and privacy, however, existing FHE deep convolutional neural network (CNN) models still face some issues such as low accuracy, high encryption/decryption latency, energy inefficiency, long feature extraction times, and significant cipher-image expansion. …”
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Precision Oncology Program (POP), an observational study using real-world data and imaging mass cytometry to explore decision support for the Molecular Tumor Board: study protocol by Charles Lu, Andreas Wicki, Shemra Rizzo, Dominik Glinz, Eva Camarillo-Retamosa, Laura Amanda Boos, Christian Doerig, Gabriele Gut, Nicola Miglino, Luis Fábregas Ibáñez, Charlotta Schärfe Fruechtenicht, Nandini Chitale, Martin Zoche, Bernd Bodenmiller, Stephane Chevrier, Alexandra Sophia Eklund, Marta Nowak, Sepehr Rahmani Khajouei, Carmen Galani Berardo, Lukasz Kaczmarek, Karin Bosshard, William Archey, Matthias Bodmer, Chiara Louisa Hempel, Parisa Rahimzadeh, Benedict Gosztonyi, Ulrich Richter, Lorenz Bankel

“…In this case, a signed general consent form must be available. Data privacy is ensured by unique patient numbers for pseudo-anonymised data. …”
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Efficient secure federated learning aggregation framework based on homomorphic encryption by Shengxing YU, Zhong CHEN

“…In order to solve the problems of data security and communication overhead in federated learning, an efficient and secure federated aggregation framework based on homomorphic encryption was proposed.In the process of federated learning, the privacy and security issues of user data need to be solved urgently.However, the computational cost and communication overhead caused by the encryption scheme would affect the training efficiency.Firstly, in the case of protecting data security and ensuring training efficiency, the Top-K gradient selection method was used to screen model gradients, reducing the number of gradients that need to be uploaded.A candidate quantization protocol suitable for multi-edge terminals and a secure candidate index merging algorithm were proposed to further reduce communication overhead and accelerate homomorphic encryption calculations.Secondly, since model parameters of each layer of neural networks had characteristics of the Gaussian distribution, the selected model gradients were clipped and quantized, and the gradient unsigned quantization protocol was adopted to speed up the homomorphic encryption calculation.Finally, the experimental results show that in the federated learning scenario, the proposed framework can protect data privacy, and has high accuracy and efficient performance.…”
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KAB: A new k-anonymity approach based on black hole algorithm by Lynda Kacha, Abdelhafid Zitouni, Mahieddine Djoudi

“…K-anonymity is the most widely used approach to privacy preserving microdata which is mainly based on generalization. …”
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Edge Computing Oriented Certificateless Sorting Ciphertext Retrieval Scheme by DUAN Jie, GU Wei, ZHANG Shujuan, GONG Xin

“…[Purposes] In order to ensure the privacy and retrievability of cloud data, ciphertext retrieval technology has emerged. …”
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Neuroethical issues in adopting brain imaging for personalized chronic pain management: Attitudes of people with lived experience of chronic pain by Karen Deborah Davis, Monica de Oliveira, Ariana Besik, Daniel Z. Buchman

“…However, they worried that brain scans could be used to dismiss their pain self-report. Most respondents felt there were policies to protect their brain data, but 40% were concerned about privacy and brain scan use against them by their employers/insurers. …”
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Ethical Challenges in Blood Donation from Viewpoint of Blood Transfusion Policymakers, Experts and Stakeholders: A Qualitative Study by forouzan akrami, Abolfazl Asghari, tooran mohammadi, abbas sedaghat

“…Purposeful sampling and focus group discussion were used to collect data. Data analysis was performed by Graneheim and Lundman inductive content analysis. …”
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Optimizing Industrial IoT Data Security Through Blockchain-Enabled Incentive-Driven Game Theoretic Approach for Data Sharing by Muhammad Noman Sohail, Adeel Anjum, Iftikhar Ahmed Saeed, Madiha Haider Syed, Axel Jantsch, Semeen Rehman

“…However, in the Industrial Internet of Things (IIoT), the sharing of data has bandwidth, computational, and privacy issues. …”
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Decades in the Making: The Evolution of Digital Health Research Infrastructure Through Synthetic Data, Common Data Models, and Federated Learning by Jodie A Austin, Elton H Lobo, Mahnaz Samadbeik, Teyl Engstrom, Reji Philip, Jason D Pole, Clair M Sullivan

“…The same way that drug trials require infrastructure to support their conduct, digital health also necessitates new and disruptive research data infrastructure. Novel methods such as common data models, federated learning, and synthetic data generation are emerging to enhance the utility of research using RWD, which are often siloed across health systems. …”
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Analyzing the concept of solitude with the spatial syntax technique in the spatial organization of rural homes; case Study: Bushehr province by Farshid Mesbah, Behzad Vasigh, Mostafa Masoudinezhad

“…In the next stage, graph analysis technique was used to extract data from the drawn maps using tools such as connectivity, relationship, step depth, metric depth, and angle of view with the help of Depth Map software for sample analysis. …”
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A secure and efficient user selection scheme in vehicular crowdsensing by Min Zhang, Qing Ye, Zhimin Yuan, Kaihuan Deng

“…At present, user selection schemes have the following lacks: (1) Privacy protection and data security are often neglected, resulting in reduced user participation willingness. (2) Insufficient data quality assurance and challenges in processing high-dimensional redundant data remain significant issues. (3) Key exchange protocols rely on traditional cryptographic algorithms, which struggle to comply with Chinese cryptographic standards and incur high overhead. …”
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Integrating Visual Cryptography for Efficient and Secure Image Sharing on Social Networks by Lijing Ren, Denghui Zhang

“…This prevalence poses challenges for secure image forwarding, as it is susceptible to privacy leaks when sharing data. While standard encryption algorithms can safeguard the privacy of textual data, image data entail larger volumes and significant redundancy. …”
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BANK INDONESIA’S ROLE IN MITIGATING ISSUES OF MONETARY ECONOMIC SOVEREIGNTY AND HUMAN RIGHTS by Dara Salsabila

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New cross-layer reputation mechanism for mobile cloud computing by Mengyang YU, Hui LIN, Youliang TIAN

“…Users are facing increasingly serious security threats such as data leakage and privacy exposure while using various mobile cloud services.Based on the data security and privacy protection for mobile cloud computing research background,combining the cross-layer design and credit mechanism,in the node between the introduction of the MAC layer and network layer in the process of credit evaluation of factors affecting user reputation,to identify and manage internal malicious nodes.The credibility of the simulation results show that the proposed mechanism can effectively resist the internal defamation and multilayer attack,enhance the credibility of mobile terminals,thus improve the mobile cloud service data security and privacy protection.…”
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WiFi-Based Location Tracking: A Still Open Door on Laptops by Mariana Cunha, Ricardo Mendes, Yves-Alexandre de Montjoye, Joao P. Vilela

“…Location privacy is a major concern in the current digital society, due to the sensitive information that can be inferred from location data. …”
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