quotEfficient Hierarchical Data Aggregation In Wireless Sensor Networks In The Presence Of Attacksquot

Abstract

Wireless sensor network incorporates a large range of low-cost nodes that exhibits significant advantage in terms of sensing, communication, and computation capabilities. Due to limited resources in node, it is necessary to reduce the data transmission rate with an increasing average lifetime of the network. However, communication between nodes utilizes a large range of WSN energy. To minimize energy consumption, data aggregation is adopted for combining data in a sensor network to minimize the data transmission rate. Consequently, data aggregation significantly minimizes consumed energy with the elimination of data transmission back to the base station. Generally, a wireless sensor network is deployed in a hostile and remote environment for sensitive information transmission. Those sensor nodes are subjected to compromise attacks and security challenges like confidentiality of data, freshness, and integrity. This research focused on secure data aggregation in WSN for effective data aggregation and security. Initially, to achieve secure data aggregation this research adopts synopsis diffusion. In synopsis diffusion, nodes are classified with multiple rings with the determination of hop count. The node hopping count is calculated from the base station. The synopsis is scattered in multiple paths for the provision of robustness. In this research investigation, the Synopsis diffusion framework is augmented with Message Authentication Codes to combat attacks caused by compromised nodes.In the next stage, a lightweight approach for the detection of a malfunctioning node is constructed. The proposed lightweight model is defined as the Lightweight Method to avoid Malfunctioning Node (LMMN). The LMMN model focused on the reduction of the computation process. The proposed LMMN performance relies on symmetric cryptography. A pair-wise key is generated by the key server for secure data transmission between nodes and the base station with a reduced computational cost.