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Data aggregation in wireless sensor networks refers to acquiring the sensed data from the sensors to the gateway node. It reduces the amount of power consumed during data transmission between the sensor nodes. Generally homomorphic encryptions have been applied to conceal communication during aggregation. Since enciphered data can be aggregated algebraically without decryption. Here adversaries are able to forge aggregated results by compromising them. However, these schemes are not satisfying multi-application environments, provide insecure transmission and do not provide secure counting for unauthorized aggregation attacks. In this paper, we propose a new concealed data aggregation scheme extended from homomorphic privacy encryption system. The proposed scheme designed for a multi-application environment, mitigates the impact of compromising attacks in single application environments and also it can avoid the damage from unauthorized aggregations by the privacy homomorphic encryption scheme.
Wireless Sensor Networks (WSNs) rely on in-network aggregation for efficiency, however, this comes at a price: A single adversary can severely influence the outcome by contributing an arbitrary partial aggregate value. Secure in-network aggregation c
Recently, many researchers have studied efficiently gathering data in wireless sensor networks to minimize the total energy consumption when a fixed number of data are allowed to be aggregated into one packet. However, minimizing the total energy con
In wireless sensor networks (WSNs), the Eschenauer-Gligor (EG) key pre-distribution scheme is a widely recognized way to secure communications. Although connectivity properties of secure WSNs with the EG scheme have been extensively investigated, few
We propose an algorithm which produces a randomized strategy reaching optimal data propagation in wireless sensor networks (WSN).In [6] and [8], an energy balanced solution is sought using an approximation algorithm. Our algorithm improves by (a) whe
Resource and cost constraints remain a challenge for wireless sensor network security. In this paper, we propose a new approach to protect confidentiality against a parasitic adversary, which seeks to exploit sensor networks by obtaining measurements