Pre-Vaccination and Quarantine Approach for Defense Against Worms Propagation of Malicious Objects in Wireless Sensor Networks

Introduction

Wireless Sensor Network (WSN) is a collection of self-organized sensor nodes. A sensor node is composed of sensor, processor, battery and transmission units. The node may also include many other components depending upon their utility. These nodes are deployed in the hostile field and cater to issues related to deployment, coverage and connectivity (Hossain, Chakrabarti & Biswas, 2012). Extensive applications of wireless sensor network include target tracking, battlefield, biological monitoring and surveillance etc. (Akyildiz, Su, Sankarasubramaniam & Cayirci, 2002). Each sensor node collects data from the surrounding within sensing range and delivers to the sink node through adjacent nodes in a multi-hop manner. Sink node is equipped with more powerful (in terms of Energy, higher Communication range and Computing) in comparison to other sensor nodes. The sensor node is a resource restraint device. Therefore, there are certain limitations associated with these nodes. Due to these limitations, sensor nodes are vulnerable and possess weak defense capability against malicious code (worms, virus and malicious active content etc.) attack. A single conciliated node can spread the worms through adjoining nodes to the entire network. A malicious code such as worms in the WSN is one of the key threats (Pradip, Liu & Sajal, 2006) to the network protection. Hence, it is a challenging task to control the worm propagation in the WSN.

For provisioning of security mechanism against worms attacks, it is important to apprehend the worm propagation dynamics in WSN (Shrivastava, 2017; Shrivastava & Gupta, 2014). Thus, for analysis of worm propagation, mathematical modelling becomes a vital tool. When a single node gets infected by the worm then the entire network may come under threat (Liang, Musaloiu & Terzis, 2008). There is a close similitude amid software created worms and biological worms. Latest categories of worms surfaced in the recent years and they do not need an internet connection for their transmission. These categories of worms can spread from wireless communication, for instance, Bluetooth or Wi-Fi communication modes. A type of worm Cabir transmits itself constantly in Bluetooth equipped devices. Another type of worm, Mabir, has the potential to spread through Bluetooth and multimedia messaging service. Cabir and Mabir worm propagation nature is epidemic (Tang & Mark, 2009). It has been observed that worm propagation in the computer network from device to device is similar to that among people in the society (Newman, 2002; Moreno, Nekovee & Vespignani, 2004). Therefore, security measures that can shield sensor nodes against malicious signal assaults are of immense significance among researchers working on sensor network security aspects. To protect the sensor nodes against these categories of malicious signal assaults, we intend to develop a protection mechanism based on epidemic theory. Currently, lifetime and security of a WSN is one of the prime research areas. Epidemic theory for the study of malicious code spread in WSN is widely used. The goal of this work is to demonstrate a robust protection technique and, to analyze the impact of vaccination and quarantine state in the sensor network.

This paper will provide a platform for others to undertake feasibility analysis of epidemic concept for sending information in the wireless sensor network. By stating that epidemic modelling in WSN is purposeful and relevant, we make a categorization in existing model in order to justify that the proposed model works fine to control malware propagation. Experimental results support the analytical result of our model and push further research directions. The validity of this model is effectively justified with the help of simulation. The remaining section of the manuscript is structured as next section includes background, then describes the proposed model and its analysis, after that presents the Simulation and performance analysis of the model, then a comparative study is discussed and at the end, the conclusion of presented work and future scope.