A Communication-Efficient Distributed Matrix Multiplication Scheme with Privacy, Security, and Resiliency by Tao Wang, Zhiping Shi, Juan Yang, Sha Liu

“…Inspired by the application of repairing Reed–Solomon (RS) codes in distributed storage and secret sharing, we propose SDMM schemes with reduced communication overhead through the use of trace polynomials. Specifically, these schemes are designed to address three critical concerns: (i) ensuring information-theoretic privacy against collusion among servers; (ii) providing security against Byzantine servers; and (iii) offering resiliency against stragglers to mitigate computing delays. …”
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Light weighted privacy protection ViT inference framework based on secret sharing by MA Min, FU Yu, HUANG Kai, JIA Xiaofeng

“…The ViT (vision transformer) inference framework, which was widely used in image processing, was found to have a risk of leaking user privacy data. …”
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Privacy Issues, Attacks, Countermeasures and Open Problems in Federated Learning: A Survey by Blessing Guembe, Sanjay Misra, Ambrose Azeta

“…Aim This study presents a cutting-edge survey on privacy issues, security attacks, countermeasures and open problems in FL.Methodology The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach was used to determine the research domain, establish a search query, and analyze all retrieved articles from the selected scientific databases (i.e. …”
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FairRAG: A Privacy-Preserving Framework for Fair Financial Decision-Making by Rashmi Nagpal, Unyimeabasi Usua, Rafael Palacios, Amar Gupta

“…These improvements were maintained when using differentially private synthetic data, thus indicating robust privacy and accuracy trade-offs.…”
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Eisdspa: An Efficient and Secure Blockchain-Based Donation Scheme With Privacy Protection and Auditability by Yong Zhou, Hong Lei, Zijian Bao

“…Specifically, we introduce an identity credential system that facilitates anonymous donations, shielding the identities of both donors and donees through the use of BBS+ signatures and zero-knowledge proofs of knowledge (ZKPoKs). …”
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Synergistic Disruption: Harnessing AI and Blockchain for Enhanced Privacy and Security in Federated Learning by Sandi Rahmadika, Winda Agustiarmi, Ryan Fikri, Bruno Joachim Kweka

“…Blockchain technology makes self-executing agreements possible by enabling smart contracts, which reduce the need for middlemen and increase efficiency by precisely encoding contractual terms in code. By using AI oracles, these contracts can communicate with outside data sources and make well-informed decisions based on actual occurrences. …”
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Sharing images of children on social media: British motherhood influencers and the privacy paradox. by Katherine Baxter, Barbara Czarnecka

“…This study examines the extent to which popular British motherhood influencers infringe on their children's privacy by posting images of them online. We conducted a content analysis of 5,253 Instagram posts from ten UK-based influencers, supplemented by self-reported data from these influencers. …”
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A lightweight and secure authentication and privacy protection scheme for internet of medical things by Sanjay Kumar, Kumar Abhishek, Shitharth Selvarajan

“…However, transmitting sensitive patient data through IoMT devices raises significant security and privacy concerns. …”
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The Looming Privacy Challenges Posed by Commercial Satellite Imaging: Remedies and Research Directions by Nathanael Denis, Roberto Di Pietro

“…While these technologies benefit applications such as natural disaster monitoring and precision agriculture, they also introduce novel privacy risks. This perspective paper provides several contributions: we start by analyzing privacy risks using the LINDDUN privacy framework, categorizing threats like linking, identification, and data disclosure. …”
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Self-Disclosure on Professional Social Networking Sites: A Privacy Calculus Perspective by Imairi Eitiveni, Achmad Nizar Hidayanto, Yuvitri Annisa Dwityafani, Larastri Kumaralalita

“…A model contextualizing privacy calculus theory combined with the trust factor was developed and evaluated using 661 quantitative data collected through a questionnaire. …”
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Privacy preserving strategies for electronic health records in the era of large language models by Jitendra Jonnagaddala, Zoie Shui-Yee Wong

“…Risks can be reduced by using strategies like privacy-preserving locally deployed LLMs, synthetic data generation, differential privacy, and deidentification. …”
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Enhancing Privacy in IoT Networks: A Comparative Analysis of Classification and Defense Methods by Ahmet Emre Ergun, Ozgu Can, Murat Kantarcioglu

“…Therefore, the study examines privacy risks associated with sequential IoT device data and evaluates the effectiveness of ML algorithms using two datasets. …”
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CropsDisNet: An AI-Based Platform for Disease Detection and Advancing On-Farm Privacy Solutions by Mohammad Badhruddouza Khan, Salwa Tamkin, Jinat Ara, Mobashwer Alam, Hanif Bhuiyan

“…The integration of a differential privacy algorithm into our CropsDisNet model could establish the benefits of automated crop disease classification without compromising on-farm data privacy by reducing training data leakage. …”
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A content review of COVID-19-related apps used in Vietnam by Linh Tran, Federica Cucé, Nguyen Thanh An, Kadek Agus Surya Dila, Nguyen Hai Nam, Doan Le Nguyet Cat, Lee Wei Jun, Farrukh Ansar, Fatima Abdallh, Au Vo, Nguyen Tien Huy

“…The most serious user concerns were privacy breaches during data recording and storage, technical issues, and non-user-friendly interfaces. …”
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Secure distributed data integrity auditing with high efficiency in 5G-enabled software-defined edge computing by Dengzhi Liu, Zhimin Li, Dongbao Jia

“…The auditing results of the distributed data in the proposed scheme can be used as an important basis for evaluating the trustworthiness of the edge devices. …”
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MKD-Net: A Novel Neuro Evolutionary Approach for Blockchain-Based Secure Medical Image Classification Using Multi-Kernel DLM by Virendra P. Vishwakarma, Abhay Kumar Yadav

“…Moreover, the integration with blockchain provide secure feature storage and also ensures data integrity, traceability, and enhanced privacy. …”
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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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PrivItem2Vec: A privacy-preserving algorithm for top-N recommendation by Zhengqiang Ge, Xinyu Liu, Qiang Li, Yu Li, Dong Guo

“…To significantly protect the user’s privacy and prevent the user’s preference disclosure from leading to malicious entrapment, we present a combination of the recommendation algorithm and the privacy protection mechanism. …”
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FL-QNNs: Memory Efficient and Privacy Preserving Framework for Peripheral Blood Cell Classification by Meenakshi Aggarwal, Vikas Khullar, Nitin Goyal, Bhavani Sankar Panda, Hardik Doshi, Nafeesh Ahmad, Vivek Bhardwaj, Gaurav Sharma

“…Then implement the federated learning (FL) framework with IID (Independent and identically distributed) and Non-IID datasets maintain similar results by preserving data. Further FL-QNNs approach is used with these baseline models and achieved 98-99% accuracy and while optimizing memory, preserving data and resources. …”
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A Telehealth Privacy and Security Self-Assessment Questionnaire for Telehealth Providers: Development and Validation by Leming Zhou, Robert Thieret, Valerie Watzlaf, Dilhari DeAlmeida, Bambang Parmanto

“…The assessment results may be used to identify possible vulnerabilities in telehealth systems and practice or demonstrate to patients the sufficient security and privacy protection to patients’ data.…”
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