Abstract

In the process of data aggregation, intruder nodes and compromised nodes may decrease the system performance. Hence, security plays an important role. Secret sharing is a method to find the compromised nodes. The previous researches in secure data aggregation concentrated on key authentication process and little research is done in N-party secret sharing methods. In this article, we proposed quantum data aggregation using secret sharing and genetic algorithm, where a node forwards data to its most trusted neighbor only. In the proposed method, a node selects n 1-hop neighbors from a list of its m 1-hop neighbors, which well behaved over a period and forwards data to the most trusted amongst them. We simulated quantum teleportation using SimulaQron tool for establishing secure communication. However secured is the communication channel the compromised nodes may decrease the system performance by exposing network to malicious activities. Each node creates n shares of a secret and forwards a share on a secured quantum channel to the n 1-hop neighbors in such a way that from any t neighbors share(t<n) the secret is reconstructed. The data aggregation security increases since a group of t users can reconstruct the key but no single user has the complete authority on the secret. The proposed method ensures that each node will be able to aggregate the captured message securely without any interventions from the compromised/intruder nodes. The proposed system applies genetic method to improve the efficiency of the process of detection of the compromised nodes based on the behavioral history of the node. While detecting the malicious nodes the proposed method accuracy rate is 98.8 and false rate is 0.15, which is almost equal to secure and energy-efficient data aggregation method based on an access control method. However, in terms of the size of the network considered, the percentage of malicious nodes assumed and from the basic principles of quantum teleportation, the proposed method proves to be a better protocol for implementing secure data aggregation.

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