Balancing Explainability and Privacy in Bank Failure Prediction: A Differentially Private Glass-Box Approach by Junyoung Byun, Jaewook Lee, Hyeongyeong Lee, Bumho Son

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A Novel Differentially Private Online Learning Algorithm for Group Lasso in Big Data by Jinxia Li, Liwei Lu

“…It proceeds to elucidate the concept of differential privacy and its importance. By enhancing the group-follow-the-proximally-regularized-leader (GFTPRL) algorithm, we have created a new method for the online group lasso model that integrates differential privacy for binary classification in logistic regression. …”
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FSPPCFs: a privacy-preserving collaborative filtering recommendation scheme based on fuzzy C-means and Shapley value by Weiwei Wang, Wenping Ma, Kun Yan

“…Recent literature predominantly employs differential privacy to achieve privacy protection, however, many schemes struggle to balance user privacy and recommendation performance effectively. …”
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Inference Attacks on Genomic Data Based on Probabilistic Graphical Models by Zaobo He, Junxiu Zhou

“…Finally, synthetic genomic dataset is sampled and it is proved that any query on synthetic dataset satisfies differential privacy guarantee.…”
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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. Depending on the task, strategies should be employed to increase compliance with patient privacy regulatory frameworks.…”
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Discussion on Artificial Intelligence Safety and Ethical Issues by Chen Xinyu, Hui Tianfang, Li Yanlin, Yang Haoyuan

“…In addition, it is recommended to adopt measures such as data encryption and differential privacy to address data privacy and security issues. …”
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EdgeGuard: Decentralized Medical Resource Orchestration via Blockchain-Secured Federated Learning in IoMT Networks by Sakshi Patni, Joohyung Lee

“…We have made several technological advances, including a lightweight blockchain consensus mechanism designed for IoMT networks, an adaptive edge resource allocation method based on reinforcement learning, and a federated learning algorithm optimized for medical data with differential privacy. We also create an access control system based on smart contracts and a secure multi-party computing protocol for model updates. …”
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A Clonal Selection Optimization System for Multiparty Secure Computing by Minyu Shi, Yongting Zhang, Huanhuan Wang, Junfeng Hu, Xiang Wu

“…Furthermore, this research attempts to improve the privacy security defense capability of the federated learning scheme for big data through differential privacy preprocessing. The simulation results show that the proposed clonal selection optimization system based on federated learning has significant optimization ability on model basic performance, stability, and privacy.…”
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Toward Privacy Preservation Using Clustering Based Anonymization: Recent Advances and Future Research Outlook by Abdul Majeed, Safiullah Khan, Seong Oun Hwang

“…The main technical solutions for guaranteeing a user’s privacy are encryption, pseudonymization, anonymization, differential privacy (DP), and obfuscation. Despite the success of other solutions, anonymization has been widely used in commercial settings for privacy preservation because of its algorithmic simplicity and low computing overhead. …”
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