1. A Visual Simulation of Compromised Node Detection in a Wireless Sensor Network
Presented by Kwame J. Martin, Computer Science, Norfolk State University
Advisor: Ms. Cheryl Hinds, Computer Science, Norfolk State University
Introduction
Wireless Sensor Networks (WSNs) are networks which consist of small
devices called sensor nodes, (also referred to as motes) each of which is
small, lightweight and portable. Every sensor is equipped with a transducer,
microcomputer, transceiver and a power source. The transducer generates
electrical signals based on sensed physical effects and phenomena. The
microcomputer processes and stores the sensed data. The transceiver, which
can be hard-wired or wireless, receives commands from a central computer
called the base station to transmit data.
Problems
WSNs face many challenges. Due to widespread use of these networks and
the importance of the information they gather, they can be targets of
malicious attacks. These attacks generally fall under two main categories:
Physical Attacks:
Jamming: a device is used to jam, that is; partially or
entirely disrupt a node’s signal
Tampering: an adversary can gain full control over some
sensor nodes through direct physical access
Network Attacks:
Sending of false information to nodes
Use of malicious nodes to block the forwarding of data
packets
Trick nodes into thinking an adversary is a neighbor
Project Goal
Importance/Significance
•Most WSN simulators only read in input data from the user, crunch numbers
and produce results in a numerical format.
•Researchers need to simulate their solution prior to implementation.
•Compromised nodes can cause serious problems in a WSN. These nodes need
to be detected.
•To create a graphical visual simulator to simulate the detection of
compromised nodes in a WSN.
•This research will benefit the field of Wireless Sensor Network research by
providing researchers and analysts with a visual WSN simulator, to show the
detection of compromised nodes in a WSN by first implementing energy
efficient algorithms which detect compromised nodes.
Methodology
•Investigated current simulators to determine if there was one that we
could modify to add a feature to detect compromised nodes in a WSN.
•Downloaded DarkGDK, the DarkBASIC Professional engine packaged up
for use with Visual C++. DarkBASIC is a commercial game creation
programming library released by a company called The Game Creators.
•Researched the DarkGDK library and capabilities to determine:
•How to display user interface
•How to intentionally compromise nodes and make some
nodes trusted
•How to display nodes on screen
•How determine nodes as neighbors
•Code to draw network
WSN Simulator
Interface of Wireless Sensor Network Simulator
Results
•What we have created is a 2D visual simulation of what the WSN network
would look like given the coordinates provided by Ms. Hinds.
•You can see where the trusted nodes are drawn in white, the compromised
nodes in red and the nodes that neither compromised nor trusted in
magenta. All nodes are connected to their neighbors by a straight white line.
Discussion
•The X and Y coordinates within the 100 x 100 max size ranges are used in
DarkGDK’s dbCircle(x, y, radius) to depict nodes being deployed at their
various locations in the network. The color key helps to visually simulate
the actual compromising and trusting of the nodes in the WSN, and
their detection.
Conclusion
•Future Work:
 The adding of a module to simulate Power Consumption
of individual nodes to show the power level of an
individual node.
 Testing our design with a series of human subjects, to
help enhance our simulation design to make it as user-
friendly as possible.
 Since we utilized a game creating programming
language, DarkGDK, one thing that can be done to
improve on our simulation is to make our creation 3D.
Acknowledgements
I would like to give special thanks to my advisor Ms. Cheryl Hinds for
her assistance. I would also like to acknowledge and give special thanks
to the grant that funded my research project, grant number DE-FG52-
09NA29516 of the Establish a Massie Chair of Excellence in Information
Assurance and Cyber Security. Special thanks to Dr. Jonathan Graham,
the director of the Information Assurance Research, Education and
Development Institute at Norfolk State University.
References
[1] Bojkovic, Zoran S., Bojan M. Bakmaz, and Miodrag R. Bakmaz. "International Journal of Communication." Security Issues in Wireless Sensor Networks
(2008). Web. 17 Nov. 2010
[2] Becher, Alexander. "Tampering with Motes." Tampering with Motes: Real-World Physical Attacks on Wireless Sensor Networks. Web. 7 Dec. 2010.
[3] Chan, Haowen. "Security and Privacy in Sensor Networks." Security and Privacy in Sensor Networks. Web. 7 Dec. 2010.
[4] Cook, D. J., S. K. Das, and John Wiley. "Smart Environments: Technologies, Protocols, and Applications." Wireless Sensor Networks. Web. 10 Dec. 2010.
[5] D. Li, K. D. Wong, Y. H. Hu, and A. M. Sayeed, “Detection, classification, and tracking of targets”, IEEE Signal Processing Mag., vol. 19, pp. 17-29, Mar
2002.
[6] Egea-López, E., J. Vales-Alonso, A. S. Martínez-Sala, P. Pavón-Mariño, and J. García-Haro. "Summer Simulation Multiconference." Simulation Tools for
Wireless Sensor Networks (2005). Web. 17 Nov. 2010.
[7] Efficient Detection of Compromised Nodes in a Wireless Sensor Network, C. Hinds, , 12th Annual Communications and Networking Simulation
Symposium (CNS), 2009.
[8] Kalita, Hermanta K., and Avijit Kar. “Wirelesss Sensor Network Security Analysis.” International Journal of Next- Generation Networks (IJNGN), Web.
12 Feb. 2011.
[9] Karlof, Chris. "Secure Routing in Wireless Sensor Networks: Attacks and Countermeasures." Secure Routing in Wireless Sensor Networks: Attacks and
Countermeasures. Web. 7 Dec. 2010.
[10] A. Mainwaring, J. Polastre, R. Szewczyk, D. Culler, and J.Anderson, “Wireless sensor networks for habitat monitoring”, Inacm Inter. Workshop on
Wireless Sensor Networks and Applications (WSNA'02), Atlanta, GA, 2002.
[11] Muraleedharan, Rajani. "Jamming Attack Detection and Countermeasures In Wireless Sensor." Jamming Attack Detection and Countermeasures In
Wireless Sensor. Web. 7 Dec. 2010.
[12] Parbat, Bhawana. "Data Visualization Tools for WSNs: A Glimpse." Www.ijcaonline.org. International Journal of Computer Applications, May-June
2005.
[13] Römer, Kay, Friedemann Mattern "The Design Space of Wireless Sensor Networks", IEEE Wireless Communications, Dec. 2004.
[14] Scaling, By. "Energy-Efficient Algorithms | May 2010." Communications of the ACM. Web. 11 Oct. 2010.
[15] Stein, David J. "Wireless Sensor Network Simulator." Djstein.com. 23 Mar. 2005. Web. 18 Nov. 2010
[16] "Wireless Sensor Networks Research Group." Computer Science at Western Michigan University. Web. 11 Oct. 2010.
[17] "What Is Sensor Network?" Data Center Information, News and Tips - SearchDataCenter.com. Tech Target. Web. 17 Nov. 2010.
[18] Wang, Qin. "A Realistic Power Consumption Model for Wireless Sensor Network Devices." Division of Engineering and Applied Sciences Harvard
University. Web. 11 Oct. 2010.
[19] Xing, Kai. "Real-time Detection of Clone Attacks in Wireless Sensor Networks." Real-time Detection of Clone Attacks in Wireless Sensor Networks.
Web. 7 Dec. 2010.
[20] Yussoff, Yusnani. "Trusted Wireless Sensor Node Platform." Www.iaeng.org. Proceedings of the World Congress on Engineering, June-July 2010.