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Abstract The rapid proliferation of wireless body area networks (WBANs) has intensified the need for architectures that simultaneously guarantee quantum-resistant security, patient privacy, and clinical-grade diagnostic ...

Abstract The increasing adoption of Industrial Internet of Things (IIoT) devices introduces significant cybersecurity and privacy challenges, particularly anomaly detection and secure data sharing. This study presents Se...

Abstract The ability to monitor the safety of natural gas pipelines is guaranteed by leak detection. Systems are capable of responding quickly, and very precisely to events because delays during such events can lead to s...

Abstract In the contemporary digital era, the storage of Electronic Health Records on open platforms presents significant security and privacy challenges. Addressing these concerns requires standardizing the clinical dep...

Abstract Differentially private stochastic gradient descent is a standard algorithm for training deep models on sensitive data, but under tight privacy budgets it must add large noise to every step, which slows convergen...

Abstract Precision oncology relies on access to high-quality data for increasingly smaller patient subgroups. The international atomCAT consortium investigates the potential of federated learning to support this, using a...

Abstract Access to large, diverse biomedical datasets is critical for advancing medical research, yet privacy regulations severely restrict data sharing. We present an end-to-end framework for privacy-preserving health d...

Abstract The explosion of patient data, the demand for real-time insights, and the critical importance of data security drive healthcare innovation. Medical Internet of Things (IoMT) offers a promising solution, connecti...

Abstract DriveEmo-FL presents a privacy-preserving, radar-based emotion-recognition framework tailored for autonomous-vehicle (AV) cabins. Leveraging a compact embedded mmWave radar, the system captures upper-body emotio...

Abstract Secure multiparty computation enables collaborative computations across multiple users while preserving individual privacy, which has a wide range of applications in finance, machine learning and healthcare. Sec...

Abstract With a growing number of institutions involved in the global education market, it has become increasingly challenging to verify the authenticity of academic documents and to match them between universities. The ...

Abstract Food spoilage significantly increases global waste, particularly for perishable goods, where maintaining real-time freshness is challenging. Monitoring and tracking food freshness ensures food safety, minimizes ...

Abstract Publicly available, large-scale medical imaging datasets are crucial for developing and validating artificial intelligence (AI) models and conducting retrospective clinical research. However, multimodal datasets...