DETECTING DENIAL OF SERVICE ATTACK IN WIRELESS SENSOR NETWORKS

ABSTRACT

Wireless sensor networks, thanks to recent technological advances, has become prevalent and offer a variety of applications ranging from environmental monitoring to support and automate chores fields. However, this very promising technology faces many inherent constraints (sensor node architecture, runtime, etc...). All these, because the network face many challenges such as energy efficiency, routing, self-organization and self-maintenance, data aggregation, security, mobility, etc. A wireless sensor network is a special case of ad hoc networks and therefore inherits certain characteristics of ad hoc networks. Due to the nature of the wireless environment, the sensor nodes face many security challenges. Intruders may enter the network and cause disruption of its normal operation. Nodes usually perform energy-saving mechanisms that allow them to switch to standby (sleep) mode from time to time. However, an evil intentioned node can join the network and thus prohibit nodes wishing enter standby mode from turning off their radio. This can be termed as sleep deprivation torture also known as Denial of sleep attacks. It is achieved by making them believe that there is data to be transmitted or just has to stay awake for monitoring. Much overhead is introduced in most of the existing works on sleep deprivation attacks detection, leading to poor performance. The need of the day is to therefore develop energy efficient methods by which the attack can be mitigated. In this work, a strong link-layer authentication and Anti-replay protection is proposed for TMAC protocol to mitigate Denial of sleep attacks. Simulation results show that our proposed mechanism is able to reduce the effects of Denial of sleep attacks in Wireless Sensor Networks.

CHAPTER 1

1.0 INTRODUCTION 1.1 Background

Wireless Sensor Network (WSN), is composed of several spatially distributed nodes, and connected to one or more sensors, which monitor a large physical environment. The nodes (wireless devices) are typically small in size and capable of performing sensing, on-board processing, communication and storage. WSNs [1] offer economically viable solutions for a variety of applications such as current implementations to monitor factory instrumentation, pollution levels, freeway traffic, and the structural integrity of buildings. Other applications include climate sensing and control in office buildings, and home environmental sensing systems for temperature, light, moisture, and motion. The Development of wireless sensor networks resulted mainly from the military applications [2] such as battlefield surveillance. In 1978, the Defense Advanced Research Projects Agency (DARPA) organized the Distributed Sensor Nets Workshop, focusing on sensor network research challenges such as networking technologies, signal processing techniques, and distributed algorithms. DARPA also operated the Distributed Sensor Networks (DSN) program in the early 1980s, which was then followed by the Sensor Information Technology (SensIT) program. Currently, WSN is viewed as one of the most important technologies for the 21st century (21 Ideas for the 21st Century, 1999). WSN is becoming a more commonplace and can be found in research projects and civilian applications as well as defense projects. The sensor nodes are often deployed to remote and inaccessible areas and thereby increase their exposure to malicious intrusions and attacks. WSN is therefore faced with several security challenges when deployed to remote areas. One of the most challenging security threats is a Denial of Service Attack (DoS) which is the result of any action that prevents any part of a WSN from functioning correctly or in a timely manner [3]. It can be viewed as a malicious attempt to make network resource unavailable to legitimate users, thus is considered one of the most general and dangerous attacks endangering network security. 4 Types of DoS attacks [4] include Jamming attack, Exhaustion attacks, Selective Forwarding attacks, Flooding, Denial of Sleep, and Sinkhole among others which will be discussed later. It is important to develop ways of preventing/detecting these attacks from occurring to get maximum functionality of the Network. A specific type of DoS is the Denial of sleep attack which comes in the form of sending useless control traffic and forces the nodes to forgo their sleep cycles so that they are completely exhausted and hence stop working [5]. This work reviews several ways of detecting the denial of sleep attacks and determines an efficient way to mitigate the attacks.

Department: Computer Science (M.Sc Thesis)

Format: MS Word

Chapters: 1 - 5, Preliminary Pages, Abstract, References, Appendix.

No. of Pages: 54 

Price: 20,000 NGN

In Stock

Buy Now

Our Customers are Happy!!!

See What Some of Our Customers are Saying About Us