Intrusion Detection in Mobile Adhoc Network with Bayesian model based MAC Identification

Mobile Ad-hoc Networks (MANETs) are a collection of heterogeneous, infrastructure less, self-organizing and battery powered mobile nodes with different resources availability and computational capabilities. The dynamic and distributed nature of MANETs makes them suitable for deployment in extreme and volatile environmental conditions. They have found applications in diverse domains such as military operations, environmental monitoring, rescue operations etc. Each node in a MANET is equipped with a wireless transmitter and receiver, which enables it to communicate with other nodes within its wireless transmission range. However, due to limited wireless communication range and node mobility, nodes in MANET must cooperate with each other to provide networking services among themselves. Therefore, each node in a MANET acts both as a host and a router. Present Intrusion Detection Systems (IDSs) for MANETs require continuous monitoring which leads to rapid depletion of a node?s battery life. To avoid this issue we propose a system to prevent intrusion in MANET using Bayesian model based MAC Identification from multiple nodes in network. Using such system we can provide lightweight burden to nodes hence improving energy efficiency

Protection of an intrusion detection engine with watermarking in ad hoc networks

Mobile ad hoc networks have received great attention in recent years, mainly due to the evolution of wireless networking and mobile computing hardware. Nevertheless, many inherent vulnerabilities exist in mobile ad hoc networks and their applications that affect the security of wireless transactions. As intrusion prevention mechanisms, such as encryption and authentication, are not sufficient we need a second line of defense, Intrusion Detection. In this pa-per we present an intrusion detection engine based on neural networks and a protection method based on watermarking techniques. In particular, we exploit information visualization and machine learning techniques in order to achieve intrusion detection and we authenticate the maps produced by the application of the intelligent techniques using a novel combined watermarking embedding method. The performance of the proposed model is evaluated under different traffic conditions, mobility patterns and visualization metrics

Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs). The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial

A Survey on Wireless Sensor Network Security

Wireless sensor networks (WSNs) have recently attracted a lot of interest in the research community due their wide range of applications. Due to distributed nature of these networks and their deployment in remote areas, these networks are vulnerable to numerous security threats that can adversely affect their proper functioning. This problem is more critical if the network is deployed for some mission-critical applications such as in a tactical battlefield. Random failure of nodes is also very likely in real-life deployment scenarios. Due to resource constraints in the sensor nodes, traditional security mechanisms with large overhead of computation and communication are infeasible in WSNs. Security in sensor networks is, therefore, a particularly challenging task. This paper discusses the current state of the art in security mechanisms for WSNs. Various types of attacks are discussed and their countermeasures presented. A brief discussion on the future direction of research in WSN security is also included.Comment: 24 pages, 4 figures, 2 table