A FRAMEWORK FOR COMPARATIVE ANALYSIS OF WSN ATTACKS AND COUNTER MEASURES RECOMMENDATIONS

Abstract

Abstract— The growth in the need for customized services in hand held devices and sensor based applications are continuously motivating the wireless networks, wireless communications and wireless infrastructures. In the last decade the wireless communication has evolved around the MANETs and IoT devices. Nevertheless, the demands for wireless sensors have not decreased due to less costly and simple deployments measures. The wireless networks especially running on the tiny operating systems are designed and programmed to perform very specific tasks. Also, the processing capabilities of these devices are limited. Henceforth, it is difficult to incorporate additional services into the devices such as routing management, data processing or security. The routing management protocols or the data processing frameworks are often the essential part of the framework. Nevertheless, due to the bottleneck between performance and service availability, the service providers ignore the security issues. Considering the wide use of the wireless sensors ranging from healthcare to tactical usage, it is the demand of the modern research to re-address the security measures of the wireless sensor network. In the recent past, the researchers and practitioners have witnessed a number of attacks on WSN infrastructures and policies. The attacks were diversified in terms of distortions of the information, damage to the network or sometimes vulnerability to the user identifications. Hence, none of the single frameworks are capable of detect all types of attacks on WSN. It is been observed that during any attacks on the WSN, the parametric values related to power, energy and response time changes drastically. Henceforth, any measure of the changes and continuous monitoring may lead to finding a pattern in the data tenting to standard formulations. Thus this work proposes a novel framework to detect the behavioural malfunction of the wireless sensor networks based on the energy, power consumption and response time of the nodes. This is proposed to be the major outcome of this work. Yet another novel outcome of this work is to associate the detection model with the attack response knowledge base in order to generate timely recommendations to avoid the damages. The objective of this work is to create a responsive system for controlling the damages caused by any attack on wireless sensor network for making the world of wireless communication more trustable.