Efficient and Privacy Preserving Similarity Range Query over Encrypted Time Series Data
To design and implement an efficient privacy-preserving framework for performing similarity range queries over encrypted time series data, ensuring data confidentiality, query accuracy, and low computational overhead while enabling secure and scalable analytics.
Project ID: 0085
Sub domains: Dependable and Secure Computing
Domain: Java
Project Year: 2022
Keywords: Encrypted Time Series Data Similarity Range Query Privacy-Preserving
Project Cost : â‚ą6500
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