Complete Merkle Hash Trees for Large Dynamic Spatial Data

被引：1
|
作者：
Adhikari, Naresh [1 ]
Bushra, Naila [1 ]
Ramkumar, Mahalingam [1 ]
机构：
[1] Mississippi State Univ, Dept Comp Sci, Mississippi State, MS 39762 USA
来源：
2019 6TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND COMPUTATIONAL INTELLIGENCE (CSCI 2019) | 2019年
关键词：
geographic information system; integrity; Merkle Hash Tree; completeness; big data;
D O I：
10.1109/CSCI49370.2019.00246
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Ensuring the integrity of big (large) and dynamic geo-spatial data is essential for assuring the correctness of queries pertaining to such 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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页码：1318 / 1323
页数：6
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