Modeling Attacks on Wireless Sensor Networks
Vikram Chilukoti and Doriel Josic
Oakland University, Department of Computer Science and Engineering, Rochester, MI 48309
Abstract- There is a consistent growth in the automation of day to day life. Wireless Sensor Networks (WSNs) play a major part in automation as they are used in almost all aspects of day to day life. At the same time, attacks on WSNs have increased gradually due to the confidential and sensitive information they always carry. Attacks on WSNs are an active research area with various workshops and conferences arranged each year. Various attacks on WSNs are discussed in this paper, and a model summarizing how the attacks fit in relation to each other is provided. This paper should clearly be able to differentiate and distinguish the attacks based on their nature.
Wireless Sensor Networks (WSNs) use sensors in the wireless network to cooperatively monitor physical or environmental conditions at different locations. These wireless networks consist of spatially distributed autonomous devices. Common implications of wireless sensor networks are environmental monitoring, habitat monitoring, acoustic monitoring, seismic monitoring, military surveillance, inventory tracking, medical monitoring, smart spaces, and process monitoring. The main advantage that makes WSN stand out is their ability to eliminate the physical involvement of a human to gather information. More research on WSN can lead to complete elimination of a human involvement in information gathering and can produce accurate results. However, one of the main fundamental research challenges for WSNs is that they are susceptible to a variety of attacks due to their wireless nature and due to them being deployed in remote areas where there is no physical security for them. The objective of this project is to research the various attacks on WSNS in order to better understand the vulnerabilities and security issues that must be addressed when trying to secure a WSN. In doing so, our goal is to provide a model of the various attack methods. All the attacks that are discussed in this paper are going to fall in one of the following layers: Physical Layer, Link Layer, Transport Layer, Application Layer and Network and Routing Layer. The rest of the paper consists of various attacks on WSNS modeled according to their similarities. Section 2 consists of the attacks in the Physical Layer, Section 3 consists of the attacks in the Link Layer, Section 4 consists of the attacks in the Transport Layer, Section 5 consists of attacks in the Application Layer, Section 6 consists of attacks in the Network and Routing Layer and Section 7 shows the visual interpretation of modeling attacks on wireless sensor networks. Finally, Section 8 concludes the paper.
I. PHYSICAL LAYER
Sensor nodes use Radio Frequency to communicate wirelessly among each other . Base stations can use wired or satellite communication, but limitations exist on their mobility and energy.
A. Jamming Attacks
Jamming is interference with the Radio Frequency used by the nodes in a network . An adversary can disrupt the communication in the entire network by using a small number of nodes scattered around in the network. However these jammers are also energy-inefficient, meaning they would exhaust their energy sooner than their victims would when given comparable energy budgets. Although random jammers save energy by sleeping, they are less effective . Following figure shows the jammed region by an adversary
JAMMED REGION DURING JAMMING ATTACK 
B. Tampering Attacks
An attacker can tamper the nodes physically to interrogate and compromise them. Large networks where a large numbers of nodes are spread within hundreds of miles can fall prey to true brute-force destruction by the attacker. An attacker can damage or replace sensor and computation hardware or extract sensitive material...
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2] C. Karlof and D. Wagner, “Secure routing in sensor networks: Attacks and countermeasures”, Ad Hoc Networks, vol 1, issues 2–3 (Special Issue on Sensor Network Applications and Protocols), pp. 293-315, Elsevier, September 2003.
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4] T. Roosta, S. Shieh, S. Sastry, “Taxonomy of Security Attacks on Sensor Networks”, IEEE International Conference on System Integration and Reliability Improvements, 2006.
5] H. Song, S. Zhu, G. Cao, “Attack-Resilient Time Synchronization for Wireless Sensor Networks”, in: IEEE MASS, 2005, pp. 765–772.
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