Ensuring the integrity of big (large) and dynamic geo-spatial data is essential for assuring the correctness of queries pertaining to tosuch data. Some useful tools towards ensuring integrity include strategies to compute a succinct cryptographic hash of well-structured data. An important requirement of such data structures is the property of completeness. We propose efficient data structures that satisfy this essential property for a wide variety of (geo) spatial data. We highlight how such data structures can be used as a foundation for assured execution of services (such as a map and geo-based web-services) that feed on spatial data.
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Complete Merkle Hash Trees for Large Dynamic Spatial Data
Semantic Scholar · Computer Science · 2019
Abstract
Ensuring the integrity of big (large) and dynamic geo-spatial data is essential for assuring the correctness of queries pertaining to tosuch data. Some useful tools towards ensuring integrity include strategies to compute a succinct cryptographic hash of well-structured data. An important requirement of such data structures is the property of completeness. We propose efficient data structures that satisfy this essential property for a wide variety of (geo) spatial data. We highlight how such data structures can be used as a foundation for assured execution of services (such as a map and geo-based web-services) that feed on spatial data.