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Deployment of sensor network in hostile environment makes it mainly vulnerable to battery drainage attacks because it is impossible to recharge or replace the battery power of sensor nodes. Among different types of security threats, low power sensor nodes are immensely affected by the attacks which cause random drainage of the energy level of sensors, leading to death of the nodes. The most dangerous type of attack in this category is sleep deprivation, where target of the intruder is to maximize the power consumption of sensor nodes, so that their lifetime is minimized. Most of the existing works on sleep deprivation attack detection involve a lot of overhead, leading to poor throughput. The need of the day is to design a model for detecting intrusions accurately in an energy efficient manner. This paper proposes a hierarchical framework based on distributed collaborative mechanism for detecting sleep deprivation torture in wireless sensor network efficiently. Proposed model uses anomaly detection technique in two steps to reduce the probability of false intrusion.

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Abstract. Security of Wireless sensor network (WSN) becomes a very important issue with the rapid development of WSN that is vulnerable to a wide range of attacks due to deployment in the hostile environment and having limited resources. Intrusion detection system is one of the major and efficient defensive methods against attacks in WSN. A particularly devastating attack is the sleep deprivation attack, where a malicious node forces legitimate nodes to waste their energy by resisting the sensor nodes from going into low power sleep mode. The goal of this attack is to maximize the power consumption of the target node, thereby decreasing its battery life. Existing works on sleep deprivation attack have mainly focused on mitigation using MAC based protocols, such as S-MAC, T-MAC, B-MAC, etc. In this article, a brief review of some of the recent intrusion detection systems in wireless sensor network environment is presented. Finally, we propose a framework of cluster based layered countermeasure that can efficiently mitigate sleep deprivation attack in WSN. Simulation results on MATLAB exhibit the effectiveness of the proposed model in detecting sleep-deprivation attacks.Keywords: WSN, Sleep Deprivation Attack, Cluster, IDS, Insomnia. IntroductionWireless sensor network (WSN) refers to a system that consists of number of low-cost, resource limited sensor nodes to sense important data related to environment and to transmit it to sink node that provides gateway functionality to another network, or an access point for human interface. WSN is a rapidly growing area as new technologies are emerging, new applications are being developed, such as traffic, environment monitoring, healthcare, military applications, home automation. WSN is vulnerable to various attacks such as jamming, battery drainage, routing cycle, sybil, cloning. Due to limitation of computation, memory and power resource of sensor nodes, complex security mechanism can not be implemented in WSN. Therefore energy-efficient security implementation is an important requirement for WSN.A sleep deprivation attack (battery drainage) is a particularly severe attack in WSN because recharging or replacing node batteries in WSN may be impossible. In this type of attack, intruder forces the sensor nodes to remain awake; so that they waste their energy. This attack imposes such a large amount of energy consumption upon the limited power sensor nodes that they stop working and give rise to denial of service through denial of sleep.In this paper a survey of on-going research activity is presented. This is followed by a comparative analysis of the recent ID schemes. This paper concludes with a glimpse of the proposed model for detecting sleep deprivation attack.

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The series "Advances in Intelligent Systems and Computing" contains publications on theory, applications, and design methods of Intelligent Systems and Intelligent Computing. Virtually all disciplines such as engineering, natural sciences, computer and information science, ICT, economics, business, e-commerce, environment, healthcare, life science are covered. The list of topics spans all the areas of modern intelligent systems and computing such as: computational intelligence, soft computing including neural networks, fuzzy systems, evolutionary computing and the fusion of these paradigms, social intelligence, ambient intelligence, computational neuroscience, artificial life, virtual worlds and society, cognitive science and systems, Perception and Vision, DNA and immune based systems, self-organizing and adaptive systems, e-Learning and teaching, human-centered and human-centric computing, recommender systems, intelligent control, robotics and mechatronics including human-machine teaming, knowledge-based paradigms, learning paradigms, machine ethics, intelligent data analysis, knowledge management, intelligent agents, intelligent decision making and support, intelligent network security, trust management, interactive entertainment, Web intelligence and multimedia.The publications within "Advances in Intelligent Systems and Computing" are primarily proceedings of important conferences, symposia and congresses. They cover significant recent developments in the field, both of a foundational and applicable character. An important characteristic feature of the series is the short publication time and world-wide distribution. This permits a rapid and broad dissemination of research results.

An Intelligent Traffic System (ITS) involves a much closer interaction between all of its components: drivers, pedestrians, public transportation and traffic management systems. Adaptive signal systems, driver advisory and route planning and automated vehicles are some of the goals set up to increase the efficiency of actual systems. Vehicular network became one of the most active and emerging fields of research during last decade. Its use in diversified applications (for example safe driving, congestion avoidance, parking assist system and even entertainment) will soon bring revolutionary changes in transportation system. In this paper we have reviewed applications of wireless sensor network towards developing an efficient system to control and manage smooth traffic flow.

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