Blockchain-Enabled Federated Learning to Enhance Security and Privacy in Internet of Medical Things (IoMT) by zahra eskandari

“…Federated learning is a distributed data analysis approach used in many IoT applications, including IoMT, due to its ability to provide acceptable accuracy and privacy. …”
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Enhancing Privacy in IoT-Enabled Digital Infrastructure: Evaluating Federated Learning for Intrusion and Fraud Detection by Amogh Deshmukh, Peplluis Esteva de la Rosa, Raul Villamarin Rodriguez, Sandeep Dasari

“…To address these issues, federated learning (FL) using a flower framework is utilized to protect the privacy of individual organizations while still collaborating through separate models to create a unified global model. …”
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A Collaborative Framework for Privacy Preserving Fuzzy Co-Clustering of Vertically Distributed Cooccurrence Matrices by Katsuhiro Honda, Toshiya Oda, Daiji Tanaka, Akira Notsu

“…In many real world data analysis tasks, it is expected that we can get much more useful knowledge by utilizing multiple databases stored in different organizations, such as cooperation groups, state organs, and allied countries. …”
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Privacy-enhanced skin disease classification: integrating federated learning in an IoT-enabled edge computing by Nada Alasbali, Jawad Ahmad, Ali Akbar Siddique, Oumaima Saidani, Alanoud Al Mazroa, Asif Raza, Rahmat Ullah, Muhammad Shahbaz Khan

“…Most existing automated detection/classification approaches that utilize machine learning or deep learning poses privacy issues, as they involve centralized computing and require local storage for data training.MethodsKeeping the privacy of sensitive patient data as a primary objective, in addition to ensuring accuracy and efficiency, this paper presents an algorithm that integrates Federated learning techniques into an IoT-based edge-computing environment. …”
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A Reliable Application of MPC for Securing the Tri-Training Algorithm by Hendra Kurniawan, Masahiro Mambo

“…Due to the widespread use of distributed data mining techniques in a variety of areas, the issue of protecting the privacy of sensitive data has received increasing attention in recent years. …”
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Automated redaction of names in adverse event reports using transformer-based neural networks by Eva-Lisa Meldau, Shachi Bista, Carlos Melgarejo-González, G. Niklas Norén

“…Because the Yellow Card data contained few names, we used predictive models to select narratives for training. …”
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Improved Denclue Outlier Detection Algorithm With Differential Privacy and Attribute Fuzzy Priority Relation Ordering by Huangzhi Xia, Limin Chen, Dongyan Wang, Xiaotong Lu

“…Firstly, the differential privacy technology is used to add the Laplacian noise to the density to realize the sensitive information hiding among the data objects. …”
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How Service Quality and Perceived Privacy Can Affect the Customer Satisfaction in Generations Y and Z? by M Iqbal Nurfaizi, Endy Gunanto Marsasi

“…Data were collected by distributing questionnaires using the purposive sampling method to 190 generation Y and Z participants who used online food delivery. …”
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Explainable Federated Framework for Enhanced Security and Privacy in Connected Vehicles Against Advanced Persistent Threats by Sudhina Kumar G K, Krishna Prakasha K, Balachandra Muniyal, Muttukrishnan Rajarajan

“…The critical need for vehicular data privacy restricts traditional centralized Machine Learning (ML) approaches. …”
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An Easily Scalable Docker-Based Privacy-Preserving Malicious Traffic Detection Architecture for IoT Environments by Tong Niu, Yaqiu Liu, Qingfeng Li, Qichi Bao

“…The model is then trained using federated learning/edge computing to ensure data privacy. …”
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Privacy-Preserving U-Net Variants with pseudo-labeling for radiolucent lesion segmentation in dental CBCT by Amelia Ritahani Ismail, Faris Farhan Azlan, Khairul Akmal Noormaizan, Nurul Afiqa, Syed Qamrun Nisa, Ahmad Badaruddin Ghazali, Andri Pranolo, Shoffan Saifullah

“…To safeguard sensitive information, Differential Privacy Stochastic Gradient Descent (DP-SGD) is integrated using TensorFlow-Privacy, achieving a privacy budget of ε ≈ 1.5 with minimal performance degradation. …”
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Shape similarity differential privacy trajectory protection mechanism based on relative entropy and K-means by Suxia ZHU, Shulun LIU, Guanglu SUN

“…To solve the problem that most studies had not fully considered the sensitivity of location to privacy budget and the influence of trajectory shape, which made the usability of published trajectory poor, a shape similarity differential privacy trajectory protection mechanism based on relative entropy and K-means was proposed.Firstly, according to the topological relationship of geographic space, relative entropy was used to calculate the sensitivity of real location to privacy budget, a real-time calculation method of location sensitive privacy level was designed, and a new privacy model was built in combination with differential privacy budget.Secondly, K-means algorithm was used to cluster the release position to obtain the release position set that was most similar to the real position direction, and Fréchet distance was introduced to measure the similarity between the release track and the real track, so as to improve the availability of the release track.Experiments on real data sets show that the proposed trajectory protection mechanism has obvious advantages in trajectory availability compared with others.…”
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Sharenting in Asunción, Paraguay: Parental Behavior, Risk Perception, and Child Privacy Awareness on Social Media by María Nieto-Sobrino, Nidia Beatriz Pérez Maciel, María Sánchez-Jiménez

“…A survey of 73 parents analysed posting habits, knowledge of risks, and possible influencing factors on parental digital behaviour. Data analysis techniques such as descriptive statistics and correlation analysis were used to examine the associations between the key variables. …”
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PP-PQB: Privacy-Preserving in Post-Quantum Blockchain-Based Systems: A Systematization of Knowledge by Bora Bugra Sezer, Sedat Akleylek, Urfat Nuriyev

“…To the best of our knowledge, there is no comprehensive review or taxonomy that provides a complete picture of post-quantum secure structures with privacy-preserving techniques that have the potential to be used in blockchain. …”
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Physically secure and fog-enabled lightweight authentication scheme for WBAN by Jegadeesan Subramani, Arun Sekar Rajasekaran, Arunkumar Balakrishnan, G. Anantha Rao

“…Abstract Wireless Body Area Networks (WBANs) are vital for healthcare, fitness monitoring, and remote patient care by means of combining sensors and wearable technologies for data collection and transmission. However, ensuring secure communication in WBANs remains a critical challenge and is generally insecure against the manipulation of data, breaches of privacy, and unauthorized access. …”
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Time‐specific encrypted range query with minimum leakage disclosure by Ozgur Oksuz

“…Abstract A time‐specific encrypted range query scheme that has the following properties is proposed. (1) The proposed scheme has trapdoor privacy and data privacy so that a semi‐honest cloud is not able to get any useful information from given ciphertexts and given tokens that are used for searching ranges. (2) Unlike most of the other studies which report that the cloud server stores single encrypted keyword/element in the database, in our solution, the cloud server stores encrypted multi‐keywords/ranges in the database. …”
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Can human rights law bend mass surveillance? by Rikke Frank Joergensen

“…This paper provides a brief introduction to PRISM, continues with an outline of the right to privacy as stipulated in the International Covenant on Civil and Political Rights (ICCPR), the European Convention on Human Rights and the EU Directive on Data Protection, and moves on to discuss whether international human rights law may be used to bend mass surveillance.…”
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A Blockchain-Based Privacy Protection Model Under Quality Consideration in Spatial Crowdsourcing Platforms by Amal Albilali, Maysoon Abulkhair, Manal Bayousef, Faisal Albalwy

“…This innovative model combines the strengths of centralized efficiency and decentralized privacy, and introduces a unique mechanism that significantly enhances privacy protection and ensures data integrity. …”
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A Comparative Study of Privacy-Preserving Techniques in Federated Learning: A Performance and Security Analysis by Eman Shalabi, Walid Khedr, Ehab Rushdy, Ahmad Salah

“…Federated learning (FL) is a machine learning technique where clients exchange only local model updates with a central server that combines them to create a global model after local training. While FL offers privacy benefits through local training, privacy-preserving strategies are needed since model updates can leak training data information due to various attacks. …”
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Differential Private POI Queries via Johnson-Lindenstrauss Transform by Mengmeng Yang, Tianqing Zhu, Bo Liu, Yang Xiang, Wanlei Zhou

“…In addition, the proposed perturbation method based on the Johnson Lindenstrauss transform satisfies the differential privacy. Two popular point of interest queries, <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-NN and Range, are used to evaluate the method on two real-world data sets. …”
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