Road Distance Computation Using Homomorphic Encryption in Road Networks
Source abstract
Abstract
Road networks have been used in a wide range of applications to reduces the cost of transportation and improve the quality of related services. The shortest road distance computation has been considered as one of the most fundamental operations of road networks computation. To alleviate privacy concerns about location privacy leaks during road distance computation, it is desirable to have a secure and efficient road distance computation approach. In this paper, we propose two secure road distance computation approaches, which can compute road distance over encrypted data efficiently. An approximate road distance computation approach is designed by using Partially Homomorphic Encryption and road network set embedding. An exact road distance computation is built by using Somewhat Homomorphic Encryption and road network hypercube embedding. We implement our two road distance computation approaches, and evaluate them on the real city-scale road network. Evaluation results show that our approaches are accurate and efficient.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Cryptography and Data Security · Privacy-Preserving Technologies in Data · Vehicular Ad Hoc Networks (VANETs)
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (30)
Show source-provided references
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