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Enhancement of Concealed Data Aggregation for Multiple Applications to Prevent Vulnerabilities in Wireless Sensor Networks
Abstract
Data Aggregation is an important aspect in Wireless Sensor Networks WSNs and this is because it reduces the amount of data to be transmitted over the network. This is done by either avoiding the transmission of redundant data or aggregating the result from different sensors and forwarding only the aggregated result further to BS. In previous studies authors used homomorphic encryption properties for concealing communication during aggregation such that encrypted data can be aggregated algebraically without decrypting them. These schemes are not satisfying multi applications which lead to proposal of CDAMA (Concealed Data Aggregation for Multi Applications). It is designed for multi applications, as it provides secure counting capability and also it reduces the effect of compromising secrets of a single application. In wireless sensor networks or environments the sensor nodes are defenseless and are vulnerable to some attacks. Considering the security aspect of wireless environments we have used Dynamic Intrusion Detection Protocol Model (DYDOG) and a modified key generation procedure that uses Digital Signatures and Two Fish Algorithms along with CDAMA for enhancement of security and throughput. To prove our proposed scheme’s robustness and efficiency, we conducted the simulations, comprehensive analysis and comparisons in the end.
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