Mental health apps in India: regulatory landscape and future directions by M. I. Singh Sethi, Rakesh C. Kumar, Narayana Manjunatha, Channaveerachari Naveen Kumar, Suresh Bada Math

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EXAMINING THE IMPACT OF AI TECHNOLOGY ON MARKETING STRATEGIES IN FINANCIAL SERVICES by POPESCU JENICA, SPULBAR LUCIAN FLORIN, SMARANDESCU ANDREI

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Dynamic selectout and voting-based federated learning for enhanced medical image analysis by Saeed Iqbal, Adnan N Qureshi, Musaed Alhussein, Khursheed Aurangzeb, Atif Mahmood, Saaidal Razalli Bin Azzuhri

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Fine-tuning a local LLaMA-3 large language model for automated privacy-preserving physician letter generation in radiation oncology by Yihao Hou, Yihao Hou, Christoph Bert, Christoph Bert, Christoph Bert, Ahmed Gomaa, Ahmed Gomaa, Ahmed Gomaa, Godehard Lahmer, Godehard Lahmer, Godehard Lahmer, Daniel Höfler, Daniel Höfler, Daniel Höfler, Thomas Weissmann, Thomas Weissmann, Thomas Weissmann, Raphaela Voigt, Raphaela Voigt, Raphaela Voigt, Philipp Schubert, Philipp Schubert, Philipp Schubert, Charlotte Schmitter, Charlotte Schmitter, Charlotte Schmitter, Alina Depardon, Alina Depardon, Alina Depardon, Sabine Semrau, Sabine Semrau, Sabine Semrau, Andreas Maier, Rainer Fietkau, Rainer Fietkau, Rainer Fietkau, Yixing Huang, Yixing Huang, Florian Putz, Florian Putz, Florian Putz

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Facilitating free travel in the Schengen area—A position paper by the European Association for Biometrics by Christoph Busch, Farzin Deravi, Dinusha Frings, Els Kindt, Ralph Lessmann, Alexander Nouak, Jean Salomon, Mateus Achcar, Fernando Alonso‐Fernandez, Daniel Bachenheimer, David Bethell, Josef Bigun, Matthew Brawley, Guido Brockmann, Enrique Cabello, Patrizio Campisi, Aleksandrs Cepilovs, Miles Clee, Mickey Cohen, Christian Croll, Andrzej Czyżewski, Bernadette Dorizzi, Martin Drahansky, Pawel Drozdowski, Catherine Fankhauser, Julian Fierrez, Marta Gomez‐Barrero, Georg Hasse, Richard Guest, Ekaterina Komleva, Sebastien Marcel, Gian Luca Marcialis, Laurent Mercier, Emilio Mordini, Stefance Mouille, Pavlina Navratilova, Javier Ortega‐Garcia, Dijana Petrovska, Norman Poh, Istvan Racz, Ramachandra Raghavendra, Christian Rathgeb, Christophe Remillet, Uwe Seidel, Luuk Spreeuwers, Brage Strand, Sirra Toivonen, Andreas Uhl

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Federated Learning Approach for Breast Cancer Detection Based on DCNN by Hussain AlSalman, Mabrook S. Al-Rakhami, Taha Alfakih, Mohammad Mehedi Hassan

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Harnessing the potential of shared data in a secure, inclusive, and resilient manner via multi-key homomorphic encryption by David Ha Eun Kang, Duhyeong Kim, Yongsoo Song, Dongwon Lee, Hyesun Kwak, Brian W. Anthony

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An Efficient Secure Data Aggregation Based on Homomorphic Primitives in Wireless Sensor Networks by Qiang Zhou, Geng Yang, Liwen He

“…The scheme adopts a symmetric-key homomorphic encryption to protect data privacy and combines it with homomorphic MAC synchronically to check the aggregation data integrity. …”
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A Privacy Preserving Method in WSN by Ping Qian, Meng Wu

“…This paper surveyed the general privacy preserving methods from two aspects of location privacy and data privacy in WSN and analyzed their theories and characteristics. …”
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Privacy protection scheme of DBSCAN clustering based on homomorphic encryption by Chunfu JIA, Ruiqi LI, Yafei WANG

“…In order to reduce the risk of data privacy leakage in the process of outsourced clustering, a privacy protection scheme of DBSCAN clustering based on homomorphic encryption was proposed.In order to encrypt the float data in the actual scene, three data preprocessing methods for different data accuracy were given, and a policy for choosing a proper data preprocessing method based on data characteristics, accuracy and computational cost was also proposed.For the ciphertext comparison operation that was not supported by homomorphic encryption, a protocol between the client and the cloud server was designed to realize the function of ciphertext comparison.Theoretical analysis and experimental results show that the proposed scheme can ensure the security of data privacy, and has a higher clustering accuracy rate and lower time overhead.…”
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Research on ciphertext search for the cloud environment by Fei XIANG, Chuan-yi LIU, Bin-xing FANG, Chun-lu WANG, HONGRui-ming Z

“…Ciphertext search technology can combine the protection of user data's privacy with the efficient usage of cloud platform services. …”
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Energy-saving privacy data secure aggregation method by Yong-hao GU, Da GUO, Jiu-chuan LIN

“…For the Internet of things(IoT) secure data aggregation issues,data privacy-preserving and limited computation ability and energy of nodes should be tradeoff.Based on analyzing the pros-and-cons of current works,a low energy-consuming secure data aggregation method (LCSDA) was proposed.This method uses shortest path principle to choose neighbor nodes and generates the data aggregation paths in the cluster based on prim minimum spanning tree algorithm.Simulation results show that this method could effectively cut down energy consumption and reduce the probability of cluster head node being captured,in the same time preserving data privacy.…”
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Ultra-Short-Term Distributed Photovoltaic Power Probabilistic Forecasting Method Based on Federated Learning and Joint Probability Distribution Modeling by Yubo Wang, Chao Huo, Fei Xu, Libin Zheng, Ling Hao

“…Existing methods regarding cluster information sharing tend to easily trigger issues of data privacy leakage during information sharing, or they suffer from insufficient information sharing while protecting data privacy, leading to suboptimal forecasting performance. …”
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Federated Learning Lifecycle Management for Distributed Medical Artificial Intelligence Applications: A Case Study on Post-Transcatheter Aortic Valve Replacement Complication Predi... by Min Hyuk Jung, InSeo Song, KangYoon Lee

“…Nevertheless, existing legal frameworks and concerns regarding data privacy associated with medical information impose substantial constraints on implementing AI solutions in this domain. …”
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Blockchain data sharing scheme based on localized difference privacy and attribute-based searchable encryption by Tao FENG, Liqiu CHEN, Junli FANG, Jianming SHI

“…Aiming at the problem that traditional cloud-based data sharing schemes rely on trusted third parties and only focus on data privacy protection or access control, a blockchain data sharing scheme based on localized difference privacy and attribute-based searchable encryption was proposed.The blockchain and cloud server were combined to store data chain by chain and provide efficient, reliable and tamper-proof data sharing.Firstly, the localization difference privacy was introduced to preprocess the shared data to protect the privacy of the data owner and resist the attack of the untrusted third party.Secondly, the searchable encryption technology and attribute-based encryption were combined to realize data privacy protection, support ciphertext retrieval, and provide fine-grained access control for shared data.Finally, the safety, the correctness proof, and the experimental analysis proves that the proposed scheme meets the safety objectives.…”
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Privacy-Preserving Continual Federated Clustering via Adaptive Resonance Theory by Naoki Masuyama, Yusuke Nojima, Yuichiro Toda, Chu Kiong Loo, Hisao Ishibuchi, Naoyuki Kubota

“…With the increasing importance of data privacy protection, various privacy-preserving machine learning methods have been proposed. …”
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Research on differential privacy protection parameter configuration method based on confidence level by Senyou LI, Xinsheng JI, Wei YOU

“…In order to solve the problem that the user's real data information is disclosed during the data release and analysis process,and reduce the probability of an attacker gaining real results through differential attacks and probabilistic inference attacks,a differential privacy protection parameter configuration method based on confidence level is proposed.Analysis of attacker confidence under attacker probabilistic inference attack model and make it no higher than the privacy probability threshold set according to the data privacy attribute.The proposed method can configure more reasonable privacy protection parameters for different query privilege of query users,and avoids the risk of privacy disclosure.The experimental analysis shows that the proposed method analyzes the correspondence between attacker confidence level and privacy protection parameters based on query privilege,noise distribution characteristics and data privacy attributes,and derives the configuration formula of privacy protection parameters,which configure the appropriate parameters without violating the privacy protection probability threshold.…”
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AFM-DViT: A framework for IoT-driven medical image analysis by Jiacheng Yang

“…These results highlight the model’s robust detection accuracy while maintaining data privacy. The AFM-DViT model offers an effective solution for secure and efficient medical image analysis in IoT-enabled environments.…”
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Traffic Sign Recognition in Rainy Conditions Based on Federated Learning by Chen Yilin

“…The proposed method is demonstrated by experimental results to enhance performance in challenging weather conditions while also maintaining data privacy in machine learning applications. Overall, this paper underscores the potential of integrating federated learning with CNNs to improve traffic sign recognition capabilities.…”
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Energy-Efficient Federated Learning for Internet of Things: Leveraging In-Network Processing and Hierarchical Clustering by M. Baqer

“…It is envisaged that the proposed approach will prolong the lifespan of IoT devices and maintain high accuracy in event detection, all while ensuring robust data privacy.…”
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