Cyber-Biosecurity Challenges in Next-Generation Sequencing: A Comprehensive Analysis of Emerging Threat Vectors by Nasreen Anjum, Hani Alshahrani, Asadullah Shaikh, Mahreen-Ul-Hassan, Mehreen Kiran, Shah Raz, Abu Alam

“…Genomic data is inherently sensitive, and vulnerabilities in NGS technologies, software, data-sharing practices, and open-access databases expose it to risks concerning data confidentiality, integrity, and privacy. …”
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A Systematic Literature Review on Privacy Preservation in VANETs: Trends, Challenges, and Future Directions by Esti Rahmawati Agustina, Kalamullah Ramli, Arif Rahman Hakim, Ruki Harwahyu

“…Privacy preservation is a fundamental requirement in vehicular ad hoc networks (VANETs) because it addresses sensitive vehicle and driver data. …”
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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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An Evaluation on the Potential of Large Language Models for Use in Trauma Triage by Kelvin Le, Jiahang Chen, Deon Mai, Khang Duy Ricky Le

“…Overall, the literature highlights multifaceted applications of LLMs, especially in emergency trauma settings, albeit with clear limitations and ethical considerations, such as artificial hallucinations, biased outputs and data privacy issues. There remains room for more rigorous research into refining the consistency and capabilities of LLMs, ensuring their effective integration in real-world trauma triaging to improve patient outcomes and resource utilisation.…”
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Touch of Privacy: A Homomorphic Encryption-Powered Deep Learning Framework for Fingerprint Authentication by U. Sumalatha, K. Krishna Prakasha, Srikanth Prabhu, Vinod C. Nayak

“…Deep learning and fully homomorphic encryption (FHE) are integrated for privacy-preserving fingerprint recognition. Convolutional neural network (CNN) extract fingerprint features encrypted using the Cheon-Kim-Kim-Song (CKKS) FHE scheme. …”
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Quantum Privacy Comparison with <i>R_y</i> Rotation Operation by Min Hou, Yue Wu

“…This paper presents a novel quantum privacy comparison (QPC) protocol that employs <i>R_y</i> rotation operations to enable two participants to securely compare their binary secrets without disclosing the actual data to any party except for the comparison result. …”
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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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How Differential Privacy Will Affect Estimates of Air Pollution Exposure and Disparities in the United States by Madalsa Singh

“…Using 2010 demonstration census and pollution data, I find that compared to the original census, differentially private (DP) census significantly changes ambient pollution exposure in areas with sparse populations. …”
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Efficient and privacy-preserving multi-party skyline queries in online medical primary diagnosis by Wanjun Hao, Shuqin Liu, Chunyang Lv, Yunling Wang, Jianfeng Wang

“…By integrating our protocols with privacy matrix techniques, the cloud server can generate a comprehensive diagnostic model from multiple data sources, offering accurate diagnosis services without disclosing any users’ personal information. …”
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Cancelable Multi-Branch Deep Learning Framework for Privacy-Preserving ECG Biometric Authentication by Mohamed Hammad, Ali Abdullah S. AlQahtani, Mohammed ELAffendi, Abdelhamied A. Ateya, Nebojsa Bacanin

“…However, storing and processing raw ECG data raises privacy and security concerns, requiring advanced methods to safeguard user data. …”
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SynAdult: Multimodal Synthetic Adult Dataset Generation via Diffusion Models and Neuromorphic Event Simulation for Critical Biometric Applications by Muhammad Ali Farooq, Paul Kielty, Wang Yao, Peter Corcoran

“…We propose SynAdult, a multimodal synthetic data generation framework designed to address the scarcity of diverse and privacy-compliant senior adult face datasets for biometric applications and facial analysis. …”
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Failure of affine‐based reconstruction attack in regenerating vascular feature points by Mahshid Sadeghpour, Arathi Arakala, Stephen A. Davis, Kathy J. Horadam

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LSTM-JSO framework for privacy preserving adaptive intrusion detection in federated IoT networks by Shaymaa E. Sorour, Mohammed Aljaafari, Amany M. Shaker, Ahmed E. Amin

“…Federated learning is leveraged to enable collaborative model training across multiple IoT networks while maintaining data privacy and reducing vulnerability to data poisoning. …”
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Legal Barriers in Developing Educational Technology by Cam Ai Tran, Truc Thanh Lam Nguyen

“…Through a comparative legal analysis of domestic and international laws, the study sheds light on the legal frameworks affecting technology integration in education. Data privacy issues arise from the sensitive information collected in educational settings, while intellectual property challenges relate to protecting and fairly using digital content and software. …”
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The ethics of using artificial intelligence in medical research by Shinae Yu, Sang-Shin Lee, Hyunyong Hwang

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Enhancing Privacy by Large Mask Inpainting and Fusion-Based Segmentation in Street View Imagery by Mahdi Khourishandiz, Abdollah Amirkhani

“…Despite its reliance on accurate sensor calibration and multimodal data availability, the proposed framework offers a scalable solution for privacy-sensitive applications such as urban mapping, and virtual tourism, delivering high-quality anonymized imagery with minimal artifacts.…”
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BFG: privacy protection framework for internet of medical things based on blockchain and federated learning by Wenkang Liu, Yuxuan He, Xiaoliang Wang, Ziming Duan, Wei Liang, Yuzhen Liu

“…In this paper, we design a new privacy protection framework (BFG) for decentralized FL using blockchain, differential privacy and Generative Adversarial Network. …”
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Federated Learning-Based Trust Evaluation With Fuzzy Logic for Privacy and Robustness in Fog Computing by Thinh Le Vinh, Huan Thien Tran, Huyen Trang Phan, Samia Le

“…This paper introduces a Federated Learning Trust Model (FLTM) to assess trustworthiness across 2000 resources while preserving data privacy. FLTM incorporates six critical metrics: Availability, Reliability, Data Integrity, Identity, Computational Capability, and Throughput. …”
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Securing smart cities through machine learning: A honeypot‐driven approach to attack detection in Internet of Things ecosystems by Yussuf Ahmed, Kehinde Beyioku, Mehdi Yousefi

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An Efficient Elliptic Curve Cryptography-Based Secure Communication with Privacy Preserving for Autonomous Vehicle by Jiongen Xiao, Yi Liu, Yi Zou, Dacheng Li, Tao Leng

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