International Journal of Innovative Technology and Exploring Engineering(IJITEE) ISSN: 2278-3075, Volume-8, Issue-10, August 2019 3537 Published By: Blue Eyes Intelligence Engineering & Sciences Publication Retrieval Number J97610881019/19©BEIESP DOI: 10.35940/ijitee.J9761.0881019 Analyze The Effects of Quarantine And Vaccination on Malware Propagation in Wireless Sensor Network Satya Ranjan Biswal, Santosh Kumar Swain Abstract: Malware (worm, virus, malicious signals, etc.) propagation in Wireless Sensor Network (WSN) is one of the important concern. The WSN becomes unstable due to presence of malicious signals. Vulnerability of WSN is very high because of the structural constraint of sensor nodes. The attackers target a sensor node of WSN for malware attack. A single infected node starts to spread the malware in the entire network through neighbouring nodes. Therefore, for controlling of malware propagation in WSN a mathematical model is developed. The developed model is based on epidemic theory. The developed model consist of five states such as Susceptible-Infectious-Quarantine-Vaccination-Dead (SIQVD). The quarantine is a method through which to cease the infection spread in WSN. And through vaccination eliminate the malware from the network. The combination of quarantine and vaccination technique improves the network stability. This technique prevents malware propagation in WSN. The basic reproduction number (  ) of the model is deduced. The stability of the network depends on the value of basic reproduction number. It is found that if the value of   is less than one the network system exist in malware-fee state, otherwise in endemic state. The equilibrium points of the system is obtained. The effects of quarantine and vaccination has been analyzed on system performance. The theoretical findings are verified by simulation results. Attack Epidemic model Equilibrium point Malware propagation Security Wireless Sensor Network I INTRODUCTION Wireless Sensor Network (WSN) is a group of smart, intelligent sensor nodes. Sensor node a low-power device which is consist of an array of sensors, memory unit, processor unit, radio unit and power unit. The sensor nodes are used to sense, compute, and collect information from the physical environment. Due to confined transmission power of sensor node, the information transmit to the sink node in multi-hop manner. The sensor node is a resource constraint device. Therefore, information security is important during transmission in the network. In reality, the security of information due to malwrae attack is one of the crucial subject. The a lot of applications of WSN such as vehicle tracking, battlefield, environmental monitoring, disaster management etc. [1]. The sensor nodes are vulnerable towards malware attack [2, 3]. The security of WSN due to malware attacks is one the critical field of research. The presence of malware in WSN affects network stability, increase congestion, slow-down the operation of network, etc.[3] Revised Manuscript Received on August 05, 2019 Satya Ranjan Biswal, Associate Professor in Department of Computer Science & Engineering, Trident Academy of Technology, Bhubaneswar, Odisha. Santosh Kumar Swain, Professor in department of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, Odisha The propagation characteristics of biological worms are similar to software created worm [4]. The malwres can by easily make a target of sensor nodes due its structural limitations and lack of strong defense techniques. The attackers victimize a node of WSN, then start to spread in the entire network with the help of adjacent nodes. And disturb the smooth network operation. Therefore, this is necessary to identify infected nodes of WSN and accordingly apply corrective techniques for removal of malware from WSN. Numerous authors [2, 5, 6, 7, 8, 9] have presented the security issues in WSN due to malware attacks. They have investigated the propagation process of malware in the network on the basis of epidemic modeling. The main focus of this paper is to explain the malware propagation process and its dynamics in WSN. And developed a model that can prevent malware propagation in WSN. The developed model analyzes the effect of various states on malware propagation in WSN. The model is used the basic concept of epidemic modeling. The developed model consists of five states. The states are Susceptible-Infectious-Quarantine-Vaccination-Dead (SIQVD). The developed mechanism prevent WSN against the various types of attacks. The contributions of developed model is: • Developed a mathematical model to analyze the malware dynamics in WSN and invent technique for its elimination. • Utilize the concept of Quarantine state to restraint the malware propagation and optimize energy depletion of sensor node. • To analyze the system responsiveness and investigate the effect of vaccination on network stability. • To develop the mechanism for removal of malware from WSN and improve network stability under different conditions. The rest section of the paper is structured as: related work in Section 2; Section 3 described the formulation of the SIQVD model. Equilibrium points of the system computed in Section 4 and stability analysis of the system in Section 5. Discussion of simulation results in Section 6 and finally in Section 7 conclusions along with future study. II RELATED WORK Different types of epidemic models has been used to explain the propagation of malware in WSN. These models used the concept of epidemic theory. The epidemic theory was used for the study of biological disease spread in people [11].