Enabling Wireless Sensor Nodes for Self-Contained Jamming Detection

Authors

  • Stephan Kornemann IHP, Im Technologiepark 25, D-15236 Frankfurt (Oder), Germany
  • Steffen Ortmann IHP, Im Technologiepark 25, D-15236 Frankfurt (Oder), Germany
  • Peter Langendörfer IHP, Im Technologiepark 25, D-15236 Frankfurt (Oder), Germany
  • Alexandros Fragkiadakis Institute of Computer Science, Foundation for Research and Technology-Hellas(FORTH), Heraklion, Crete

DOI:

https://doi.org/10.13052/jcsm2245-1439.322

Keywords:

Jamming detection, Wireless sensor networks, Security

Abstract

Jamming is an easy to execute attack to which wireless sensor networks are extremely vulnerable. If the application requires reliability, jamming needs to be detected and reported in order to cope with this attack. In this article, we investigate different approaches to identify jamming. Available jamming detection schemes primarily suffer from the usage of fixed thresholds as well as required effort. We adapted a variance-based estimate of signal-to-noise ratio measurements, called significance analysis, to the minor resources and computing efforts of wireless sensor nodes. As a start, we used real measurement data for theoretical analysis of the methods under investigation. Independently of the location of the jamming device, our significance analysis approach provides an immediate indication of jamming and can in theory be run with almost least effort, i.e., with O(14). On top of that, we implemented this approach on our state of the art sensor node and tested it in a real world outdoor setting. Our jamming detection engine monitors the wireless channel with a sampling rate of 10 ms. It returns a jamming detection decision within less than 5 ms while though achieving a detection accuracy in between 84 to 99 percent.

Downloads

Download data is not yet available.

Author Biographies

Stephan Kornemann, IHP, Im Technologiepark 25, D-15236 Frankfurt (Oder), Germany

Stephan Kornemann received the M.S. degree in information and media technology from Brandenburg University of Technology, Germany, in 2012. From 2010 to 2012 he worked as software tester at Philotech and received his software testing qualification certificate from ISTQB. Since 2012 he is member of the sensor network research group at IHP in Frankfurt (Oder). His current research focuses on intrusion detection systems for wireless sensor networks.

 

Steffen Ortmann, IHP, Im Technologiepark 25, D-15236 Frankfurt (Oder), Germany

Steffen Ortmann received his diploma in computer science in 2007 and his PhD in engineering by scholarship in 2010. Since 2005 he is active in the sensor network research group of IHP. He has published more than 40 refereed technical articles about reliability, privacy and efficient data processing in wireless sensor networks and medical applications. His current research focuses on mobile wireless sensor networks for tele-medical innovations. He is coordinating the FP7 project StrokeBack and is responsible for medical driven research and the crypto-microcontroller research team within sensor networks group of IHP.

 

Peter Langendörfer, IHP, Im Technologiepark 25, D-15236 Frankfurt (Oder), Germany

Peter Langendörfer, Professor, holds a diploma and a doctorate degree in computer science. Since 2000 he is with the IHP in Frankfurt (Oder). There, he is leading the sensor networks and mobile middleware group. Since 2012 he has his own chair for security in pervasive systems at the Technical University of Cottbus. He has published more than 100 refereed technical articles, filed ten patents in the security/privacy area and worked as guest editor for many renowned journals e.g. Wireless Communications and Mobile Computing (Wiley). He was chairing International conferences such as WWIC and has served in many TPC for example at Globecom, VTC, ICC and SECON. His research interests include wireless sensor networks and cyber physical systems, especially privacy and security issues.

 

Alexandros Fragkiadakis, Institute of Computer Science, Foundation for Research and Technology-Hellas(FORTH), Heraklion, Crete

Alexandros Fragkiadakis received his PhD degree in computer networks from the Department of Electronic and Electrical Engineering of Loughborough University in UK. His thesis focused on active networks using programmable hardware (FPGAs). He has also received an MSc in Digital Communications Systems, awarded with distinction, from the same University. Alexandros obtained his Diploma degree in Electronics from the Technological Educational Institute of Piraeus. He has worked as a Research Associate within the High Speed Networks Group of Loughborough University, in a project involving active networks and field programmable gate arrays. This project was funded by the Engineering and Physical Sciences Research Council, a British Government’s leading funding agency for research and training in engineering and the physical sciences. Alexandros joined the Telecommunications and Networks Laboratory of the Institute of Computer Science of the Foundation for Research and Technology-Hellas in November 2008. His research interests include wireless networks, intrusion and anomaly detection in wireless networks, reprogrammable devices, cloud computing, open source architectures, cognitive radio networks, wireless sensor networks.

References

Wireless Communications: Principles and Practice. Prentice Hall communications engineering and emerging technologies series. Dorling Kindersley, 2009.

J.B.D. Cabrera, C. Gutierrez, and R.K. Mehra. Infrastructures and algorithms for distributed anomaly-based intrusion detection in mobile ad-hoc networks. In Military Communications Conference, MILCOM 2005. IEEE, pages 1831–1837. IEEE, 2006.

Murat Çkiroğlu and Ahmet Turan Özcerit. Jamming detection mechanisms for wireless sensor networks. In Proceedings of the 3rd international conference on Scalable information systems, InfoScale ’08, pages 4: 1–4: 8, ICST, Brussels, Belgium, 2008. ICST.

A. Fragkiadakis, V. Siris, and N. Petroulakis. Anomaly-based intrusion detection algorithms for wireless networks. In 8th International Conference on Wired/Wireless Internet Communications, pages 192–203, Lulea, Sweden, June 2010. Springer.

A. Hamieh and J. Ben-Othman. Detection of jamming attacks in wireless ad hoc networks using error distribution. In Communications, 2009. ICC ’09. IEEE International Conference on, pages 1–6, June 2009.

Texas Instruments. CC2520 DATASHEET –2.4 GHZ IEEE 802.15.4/ZIGBEE RF TRANSCEIVER.

Yu Seung Kim, Frank Mokaya, Eric Chen, and Patrick Tague. All your jammers belong to uslocalization of wireless sensors under jamming attack. In Communications (ICC), 2012 IEEE International Conference on, pages 949–954. IEEE, 2012.

Yee Wei Law, Pieter Hartel, Jerry Hartog den, and Paul Havinga. Link-layer jamming attacks on s-mac. In Proceeedings of the Second European Workshop on Wireless Sensor Networks, 2005, pages 217–225, Los Alamitos, California, 2005. IEEE Computer Society Press.

R. Muraleedharan and L.A. Osadciw. Jamming attack detection and countermeasures in wireless sensor network using ant system. SPIE Defence and Security, Orlando, 2006.

Alejandro Proano and Loukas Lazos. Selective jamming attacks in wireless networks. In Communications (ICC), 2010 IEEE International Conference on, pages 1–6. IEEE, 2010.

K.W. Reese, A. Salem, and G. Dimitoglou. Using standard deviation in signal strength detection to determine jamming in wireless networks. Computers Applications in Industry and Engineering, 2010.

Mario Strasser, Boris Danev, and Srdjan Čapkun. Detection of reactive jamming in sensor networks. ACM Transactions on Sensor Networks (TOSN), 7:16:1–16:29, September 2010.

J. Tang and P. Fan. A RSSI-based cooperative anomaly detection scheme for wireless sensor networks. In International Conference on Wireless Communications, Networking and Mobile Computing, WiCom 2007., pages 2783–2786, Shanghai, 2007.

A. D. Wood, J. A. Stankovic, and Gang Zhou. DEEJAM: Defeating Energy-Efficient Jamming in IEEE 802.15.4-based Wireless Networks. In 4th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, SECON ’07., pages 60–69, 2007.

Wenyuan Xu, Ke Ma, W. Trappe, and Y. Zhang. Jamming sensor networks: attack and defense strategies. Network, IEEE, 20(3): 41–47, May 2006.

Wenyuan Xu, Wade Trappe, Yanyong Zhang, and Timothy Wood. The feasibility of launching and detecting jamming attacks in wireless networks. In Proceedings of the 6th ACM international symposium on Mobile ad hoc networking and computing, MobiHoc, pages 46–57, NY, USA, 2005.

Downloads

Published

2014-07-10

How to Cite

1.
Kornemann S, Ortmann S, Langendörfer P, Fragkiadakis A. Enabling Wireless Sensor Nodes for Self-Contained Jamming Detection. JCSANDM [Internet]. 2014 Jul. 10 [cited 2024 Mar. 29];3(2):133-58. Available from: https://journals.riverpublishers.com/index.php/JCSANDM/article/view/6179

Issue

Section

Articles