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Keyword: Privacy-preserving
Multi Attribute Stratified Sampling: An Automated Framework for Privacy-Preserving Healthcare Data Publishing with Multiple Sensitive Attributes
The accumulation and analysis of large-scale patient data have led to breakthrough discoveries in potential flags for diseases based on pattern recognition, highlight medication efficacy, and local population health trends that would be impossible with traditional paper-based records. However, these benefits come with unique challenges posed by the application of data sharing for research and…
Read More Federated Learning with Differential Privacy and Blockchain for Security and Privacy in IoMT A Theoretical Comparison and Review
The growing integration of the Internet of Medical Things (IoMT) into healthcare has amplified the need for secure and privacy-preserving artificial intelligence. Federated Learning (FL) has emerged as a pivotal paradigm for decentralized medical data processing; however, it still faces challenges concerning data confidentiality, trust management, and scalability. This review presents an extended theoretical comparison…
Read More A Comprehensive Study of Privacy Preserving Techniques in Cloud Computing Environment
The huge growth in cloud storage utilization over the past years has made a big demand for an advanced technique and strong tools to make services even more practical and secure. Data privacy in cloud computing has become one of the biggest concerns for both individuals and organizations which adds more pressure on cloud service…
Read More A Practical PIR-based Scheme for Discovering Nearby Places for Smartphone Applications
We present a privacy-preserving approach for discovering nearby places of interest to Alice. In this approach, the proposed protocol allows Alice to learn whether there is any place that she is looking for near her. However, the location-based service (LBS) that tries to help Alice to find nearby places does not learn Alice’s location. Alice…
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