Privacy and Integrity Preserving Top-k Query Processing for Two-Tiered Sensor Networks - 2017

PROJECT TITLE :

Privacy and Integrity Preserving Top-k Query Processing for Two-Tiered Sensor Networks - 2017

ABSTRACT:

Privacy and integrity are the most road block to the applications of two-tiered sensor networks. The storage nodes, that act as a middle tier between the sensors and therefore the sink, might be compromised and allow attackers to be told sensitive data and manipulate question results. Previous schemes on secure question processing are weak, as a result of they reveal non-negligible data, and so, attackers will statistically estimate the data values using domain data and therefore the history of query results. In this paper, we have a tendency to propose the primary top-k question processing scheme that protects the privacy of sensor information and also the integrity of question results. To preserve privacy, we have a tendency to build an index for each sensor collected information item using pseudo-random hash perform and Bloom filters and transform prime-k queries into top-vary queries. To preserve integrity, we tend to propose a knowledge partition algorithm to partition each data item into an interval and fix the partition information with the data. The connected info ensures that the sink will verify the integrity of query results. We tend to formally prove that our scheme is secure below IND-CKA security model. Our experimental results on real-life data show that our approach is correct and sensible for massive network sizes.

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