Multi-function supported privacy protection data aggregation scheme for V2G network by Baiji HU, Xiaojuan ZHANG, Yuancheng LI, Rongxin LAI

“…In view of the problem that the functions of the current privacy protection data aggregation scheme were insufficient to meet the increasingly rich application requirements, a multi-function supported privacy protection data aggregation (MFPDA) scheme for V2G network was proposed.By using cryptographic algorithms such as BGN, BLS, and Shamir’s secret sharing, as well as fog computing and consortium blockchain technology, multiple security functions like fault tolerance, resistance to internal attacks, batch signature verification, no need for trusted third parties, and multiple aggregation functions were integrated into one privacy protection data aggregation scheme.Security analysis shows that the proposed scheme can protect data aggregation’s security, privacy and reliability.The performance evaluation shows that the introduction of fog computing can significantly reduce the computing overhead of the control center, and the reduction rate can be as high as 66.6%; the improvement of the consortium blockchain can effectively reduce the communication and storage overhead of the system, and the reduction rate can reach 16.7% and 24.9% respectively.…”
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A Combined Approach of Heat Map Confusion and Local Differential Privacy for the Anonymization of Mobility Data by Christian Dürr, Gabriele S. Gühring

“…Mobility data plays a crucial role in modern location-based services (LBSs), yet it poses significant privacy risks, as it can reveal highly sensitive information such as home locations and behavioral patterns. …”
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Navigating the privacy paradox in a digital age: balancing innovation, data collection and ethical responsibility by Martin Jones

“…Purpose – The purpose of this paper is to explore the intersection of generative artificial intelligence (AI), data collection and consumer privacy, highlighting ethical tensions in AI-driven advertising. …”
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Practical and privacy-preserving geo-social-based POI recommendation by Qi Xu, Hui Zhu, Yandong Zheng, Fengwei Wang, Le Gao

“…Specifically, we first utilize the quad tree to organize geographic data and the MinHash method to index social data. …”
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Privacy-preserving federated learning framework with dynamic weight aggregation by Zuobin YING, Yichen FANG, Yiwen ZHANG

“…There are two problems with the privacy-preserving federal learning framework under an unreliable central server.① A fixed weight, typically the size of each participant’s dataset, is used when aggregating distributed learning models on the central server.However, different participants have non-independent and homogeneously distributed data, then setting fixed aggregation weights would prevent the global model from achieving optimal utility.② Existing frameworks are built on the assumption that the central server is honest, and do not consider the problem of data privacy leakage of participants due to the untrustworthiness of the central server.To address the above issues, based on the popular DP-FedAvg algorithm, a privacy-preserving federated learning DP-DFL algorithm for dynamic weight aggregation under a non-trusted central server was proposed which set a dynamic model aggregation weight.The proposed algorithm learned the model aggregation weight in federated learning directly from the data of different participants, and thus it is applicable to non-independent homogeneously distributed data environment.In addition, the privacy of model parameters was protected using noise in the local model privacy protection phase, which satisfied the untrustworthy central server setting and thus reduced the risk of privacy leakage in the upload of model parameters from local participants.Experiments on dataset CIFAR-10 demonstrate that the DP-DFL algorithm not only provides local privacy guarantees, but also achieves higher accuracy rates with an average accuracy improvement of 2.09% compared to the DP-FedAvg algorithm models.…”
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Sinergi Pemanfaatan Big Data dengan Sharing Data Privacy Pengguna: Efek Menawarkan Kompensasi dalam Meyakinkan Pengguna E-Wallet by Christina Sudyasjayanti, Laili Rahmania

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Blockchain oracles for decentralized agricultural insurance using trusted IoT data by Manoj T, Krishnamoorthi Makkithaya, Narendra V. G., Vijaya Murari T

“…Initially, a method for computing the direct reputation score of IoT devices based on behavioral and data reputation is illustrated. Next, a privacy preserved decentralized oracle mechanism is designed and implemented using a masked secret sharing and secure aggregation scheme. …”
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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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Data Security Model Using (AES-LEA) Algorithms for WoT Environment by Zinah A. Al-jazaeri, Joolan Rokan Naif, Ahmad Mohamad Ghandour

“…Therefore, ensuring data privacy and protection is a major challenge for organizations and individuals. …”
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Social Engineering Threat Analysis Using Large-Scale Synthetic Data by Sellappan Palaniappan, Rajasvaran Logeswaran, Shapla Khanam, Pulasthi Gunawardhana

“…Our model achieved an accuracy of 0.8984 and an F1 score of 0.9253, demonstrating its effectiveness in detecting social engineering attacks. The use of synthetic data overcomes the problem of lack of availability of real-world data due to privacy issues, and is demonstrated in this work to be safe, scalable, ethics friendly and effective.…”
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Clinical Simulation Program for the Training of Health Profession Residents in Confidentiality and the Use of Social Networks by Alejandro Martínez-Arce, Alberto Bermejo-Cantarero, Laura Muñoz de Morales-Romero, Víctor Baladrón-González, Natalia Bejarano-Ramírez, Gema Verdugo-Moreno, María Antonia Montero-Gaspar, Francisco Javier Redondo-Calvo

“…After the course, the participants reported intending to modify their behavior when sharing patient data without their consent and with respect to how patients are informed; Conclusions: The use of advanced simulation in the training of interprofessional teams of residents is as an effective tool for initiating attitudinal change and increasing knowledge related to patient privacy and confidentiality. …”
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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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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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(<italic>r, k, &#x03B5;</italic>)-Anonymization: Privacy-Preserving Data Publishing Algorithm Based on Multi-Dimensional Outlier Detection, <italic>k</italic>-Anonymity, and <itali... by Burak Cem Kara, Can Eyupoglu, Oktay Karakus

“…The general data protection regulation (GDPR) implementation, on the other hand, has introduced extensive control over the use of individuals&#x2019; personal information and placed many limits. …”
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Security Data Aggregation with Recoverable Data in Heterogeneous Wireless Sensor Network by Lusheng Shi, Huibo Zhu, Lin Chen

“…The algorithm uses homomorphism encryption techniques based on elliptic curve to address data privacy protection, and uses an efficient aggregate signature scheme to ensure data integrity and authenticity. …”
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Navigating the EU data governance labyrinth: A business perspective on data sharing in the financial sector by Eugénie Coche, Ans Kolk, Martijn Dekker

“…With policy-making (“on the books”) centred on guaranteeing data privacy and data security whilst promoting innovation, firms face complexities when implementing this framework “on the ground”. …”
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Tabular Data Augmentation Using Artificial Intelligence: A Systematic Review and Taxonomic Framework by Mauro Henrique Lima de Boni, Iwens Gervasio Sene Junior, Ronaldo Martins da Costa

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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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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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Community views on the secondary use of general practice data: Findings from a mixed‐methods study by Annette J. Braunack‐Mayer, Carolyn Adams, Alberto Nettel‐Aguirre, Belinda Fabrianesi, Lucy Carolan, Justin Beilby, Felicity Flack

“…Abstract Introduction General practice data, particularly when combined with hospital and other health service data through data linkage, are increasingly being used for quality assurance, evaluation, health service planning and research. …”
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