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Authenticated Continuous Top-k Spatial Keyword Search on Dynamic Objects

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Security and Privacy in Social Networks and Big Data (SocialSec 2022)

Abstract

GPS location and simple notification services are becoming more advanced. This advancement enhances spatial keyword search, including content locations and textual descriptions. Cloud users may read the news and watch social media and movies while going outside. Cloud Service Provider (CSP) can handle a wide range of spatial web objects gathered from various sources for saving local computation and storage resources. However, one major issue is that the malicious CSP may provide erroneous query results due to cost concerns, accidents or a hacker attack. The current authentication techniques for the continuous moving object are cumbersome and inadequate for our scenario. We need to check the search results on the user side and verify the query results’ correctness and soundness. This paper addresses authenticating those dynamic objects’ spatialkeyword searches, whose keywords and locations vary over time. This query benefits several location-aware services, including e-commerce, potential consumer tracking, self-driving stores, and cloud technologies. MIR-tree and MIR*-tree are two novel queries authenticating data structures with low computing and transmission costs. To aid in verifying query results, we provide a verification object and propose ways to generate it. Based on a detailed experimental analysis of real data, our suggested strategies outperform.

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Correspondence to Yetneberk Zenebe Melesew .

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Melesew, Y.Z., Li, J., Miao, Y. (2022). Authenticated Continuous Top-k Spatial Keyword Search on Dynamic Objects. In: Chen, X., Huang, X., Kutyłowski, M. (eds) Security and Privacy in Social Networks and Big Data. SocialSec 2022. Communications in Computer and Information Science, vol 1663. Springer, Singapore. https://doi.org/10.1007/978-981-19-7242-3_3

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  • DOI: https://doi.org/10.1007/978-981-19-7242-3_3

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