#4362. SecVKQ: Secure and verifiable kNN queries in sensor–cloud systems

September 2026publication date
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Journal’s subject area:
Engineering
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Abstract:
Sensor–cloud has gained increasingly popularity since it bridges the physical world and the cyber world through pervasive computation. This research focuses on secure and verifiable k nearest neighbor (kNN) queries over large-scale outsourced datasets in sensor–cloud systems. Existing work in this line often incurred high computational and communication overheads, remaining far away from practical and scalable. To this end, we propose SecVKQ, a two-phase search framework, which mainly includes a preliminary screening phase and an exact search phase. The experimental results demonstrate the effectiveness of SecVKQ. Compared to the state-of-the-art work, SecVKQ achieves a speed-up of two orders of magnitude in search latency, and a savings of 50% communication cost for verification.
Keywords:
Edge computing; kNN queries; Security; Sensor–cloud systems; Verification

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