Skip to main content

Countering Mobile Signaling Storms with Counters

  • Conference paper
Internet of Things. IoT Infrastructures (IoT360 2015)

Abstract

Mobile Networks are subject to signaling storms launched by misbehaving applications or malware, which result in bandwidth overload at the cell level and excessive signaling within the mobile operator, and may also deplete the battery power of mobile devices. This paper reviews the causes of signaling storms and proposes a novel technique for storm detection and mitigation. The approach is based on counting the number of successive signaling transitions that do not utilize allocated bandwidth, and temporarily blocking mobile devices that exceed a certain threshold to avoid overloading the network. Through a mathematical analysis, we derive the optimum value of the counter’s threshold, which minimizes both the number of misbehaving mobiles and the signaling overload in the network. Simulation results are provided to illustrate the effectiveness of the proposed scheme.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. 3GPP: Study on machine-type communications (MTC) and other mobile data applications communications enhancements (release 12) (2013). 3GPP TR 23.887. http://www.3gpp.org/DynaReport/23887.htm

  2. Abdelrahman, O.H., Gelenbe, E.: Signalling storms in 3G mobile networks. In: Proceedings of IEEE International Conference on Communications (ICC), pp. 1017–1022, Sydney (2014). doi:10.1109/ICC.2014.6883453

  3. Abdelrahman, O.H., Gelenbe, E.: A data plane approach for detecting control plane anomalies in mobile networks. In: Proceedings of International Conference on Cyber Physical Systems, IoT and Sensors Networks (Cyclone), Rome (2015)

    Google Scholar 

  4. Abdelrahman, O.H., Gelenbe, E., Gorbil, G., Oklander, B.: Mobile network anomaly detection and mitigation: the NEMESYS approach. In: Gelenbe, E., Lent, R. (eds.) Information Sciences and Systems 2013. Lecture Notes in Electrical Engineering, vol. 264, pp. 429–438. Springer, Switzerland (2013). doi:10.1007/978-3-319-01604-7_42

    Chapter  Google Scholar 

  5. Amrutkar, C., Hiltunen, M., Jim, T., Joshi, K., Spatscheck, O., Traynor, P., Venkataraman, S.: Why is my smartphone slow? on the fly diagnosis of underperformance on the mobile internet. In: Proceedings of 43rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), pp. 1–8. IEEE Computer Society, Budapest (2013). doi:10.1109/DSN.2013.6575301

  6. Arbor Networks: Worldwide infrastructure security report (2014). http://pages.arbornetworks.com/rs/arbor/images/WISR2014.pdf

  7. AT&T: Best practices for 3G and 4G app development. Whitepaper (2012). http://developer.att.com/static-assets/documents/library/best-practices-3g-4g-app-development.pdf

  8. Choi, Y., Yoon, C.H., Kim, Y.S., Heo, S.W., Silvester, J.: The impact of application signaling traffic on public land mobile networks. IEEE Commun. Mag. 52(1), 166–172 (2014). doi:10.1109/MCOM.2014.6710079

    Article  Google Scholar 

  9. Coluccia, A., D’alconzo, A., Ricciato, F.: Distribution-based anomaly detection via generalized likelihood ratio test: a general maximum entropy approach. Comput. Netw. 57(17), 3446–3462 (2013). doi:10.1016/j.comnet.2013.07.028

    Article  Google Scholar 

  10. Corner, S.: Angry birds + android + ads = network overload (2011). http://www.itwire.com/business-it-news/networking/47823

  11. Donegan, M.: Operators urge action against chatty apps. Light Reading Report (2011). http://www.lightreading.com/operators-urge-action-against-chatty-apps/d/d-id/687399

  12. Ericsson: High availability is more than five nines (2014). http://www.ericsson.com/real-performance/wp-content/uploads/sites/3/2014/07/high-avaialbility.pdf

  13. Ericsson: A smartphone app developers guide: Optimizing for mobile networks. Whitepaper (2014). http://www.ericsson.com/res/docs/2014/smartphone-app-dev-guide.pdf

  14. Francois, F., Abdelrahman, O.H., Gelenbe, E.: Impact of signaling storms on energy consumption and latency of LTE user equipment. In: Proceedings of 7th IEEE International Symposium on Cyberspace safety and security (CSS), New York (2015)

    Google Scholar 

  15. Gabriel, C.: DoCoMo demands Google’s help with signalling storm (2012). http://www.rethink-wireless.com/2012/01/30/docomo-demands-googles-signalling-storm.htm

  16. Gelenbe, E.: The first decade of G-networks. Eur. J. Oper. Res. 126(2), 231–232 (2000)

    Article  Google Scholar 

  17. Gelenbe, E., Mahmoodi, T.: Energy-aware routing in the cognitive packet network. In: ENERGY, Venice (2011)

    Google Scholar 

  18. Gelenbe, E., Morfopoulou, C.: A framework for energy-aware routing in packet networks. Comput. J. 54(6), 850–859 (2011)

    Article  Google Scholar 

  19. Gelenbe, E., Timotheou, S.: Random neural networks with synchronized interactions. Neural Comput. 20(9), 2308–2324 (2008)

    Article  MathSciNet  Google Scholar 

  20. Gelenbe, E., Wu, F.J.: Large scale simulation for human evacuation and rescue. Comput. Math. Appl. 64(12), 3869–3880 (2012)

    Article  Google Scholar 

  21. Gorbil, G., Abdelrahman, O.H., Gelenbe, E.: Storms in mobile networks. In: Proceedings of 10th ACM Symposium on QoS and Security for Wireless and Mobile Networks (Q2SWinet), Montreal, pp. 119–126 (2014). doi:10.1145/2642687.2642688

  22. Gorbil, G., Abdelrahman, O.H., Pavloski, M., Gelenbe, E.: Modeling and analysis of RRC-based signalling storms in 3G networks. IEEE Trans. Emerg. Topics Comput. 4(1), 113–127 (2016). doi:10.1109/TETC.2015.2389662

    Article  Google Scholar 

  23. GSMA: Smarter apps for smarter phones, version 4.0 (2014). http://www.gsma.com/newsroom/wp-content/uploads//TS-20-v4-0.pdf

  24. Jiantao, S.: Analyzing the network friendliness of mobile applications. Technical report, Huawei (2012). http://www.huawei.com/ilink/en/download/HW_146595

  25. Ksentini, A., Hadjadj-Aoul, Y., Taleb, T.: Cellular-based machine-to-machine: overload control. IEEE Netw. 26(6), 54–60 (2012). doi:10.1109/MNET.2012.6375894

    Article  Google Scholar 

  26. Lee, P.P., Bu, T., Woo, T.: On the detection of signaling DoS attacks on 3G wireless networks. In: Proceedings of 26th IEEE Internatioanl Conference on Computer Communications (INFOCOM), pp. 1289–1297 (2007). doi:10.1109/INFCOM.2007.153

  27. Li, J., Pei, W., Cao, Z.: Characterizing high-frequency subscriber sessions in cellular data networks. In: Proceedings of IFIP Networking Conference, Brooklyn, pp. 1–9 (2013)

    Google Scholar 

  28. Maslennikov, D.: Mobile malware evolution: Part 6. Technical report, Kaspersky Lab (2013). https://securelist.com/analysis/publications/36996/mobile-malware-evolution-part-6/

  29. NSN Smart Labs: Understanding smartphone behavior in the network. White paper (2011). http://networks.nokia.com/system/files/document/nsn_smart_labs_white_paper.pdf

  30. Qian, Z., Wang, Z., Xu, Q., Mao, Z.M., Zhang, M., Wang, Y.M.: You can run, but you can’t hide: exposing network location for targeted DoS attacks in cellular networks. In: Proceedings of Network and Distributed System Security Symposium (NDSS), San Diego, pp. 1–16 (2012)

    Google Scholar 

  31. Redding, G.: OTT service blackouts trigger signaling overload in mobile networks (2013). https://blog.networks.nokia.com/mobile-networks/2013/09/16/ott-service-blackouts-trigger-signaling-overload-in-mobile-networks/

  32. Ricciato, F.: Unwanted traffic in 3G networks. ACM SIGCOMM Comput. Commun. Rev. 36(2), 53–56 (2006). doi:10.1145/1129582.1129596

    Article  Google Scholar 

  33. Ricciato, F., Coluccia, A., D’Alconzo, A.: A review of DoS attack models for 3G cellular networks from a system-design perspective. Comput. Commun. 33(5), 551–558 (2010). doi:10.1016/j.comcom.2009.11.015

    Article  Google Scholar 

  34. Sakellari, G., Morfopoulou, C., Mahmoodi, T., Gelenbe, E.: Using energy criteria to admit flows in a wired network. In: Gelenbe, E., Lent, R. (eds.) Computer and Information Sciences III, pp. 63–72. Springer, London (2013). doi:10.1007/978-1-4471-4594-3_7

    Chapter  Google Scholar 

  35. Serror, J., Zang, H., Bolot, J.C.: Impact of paging channel overloads or attacks on a cellular network. In: Proceedings of 5th ACM Workshop Wireless Security (WiSe 2006), New York, pp. 75–84 (2006). doi:10.1145/1161289.1161304

  36. Shafiq, M.Z., Ji, L., Liu, A.X., Pang, J., Wang, J.: A first look at cellular machine-to-machine traffic: large scale measurement and characterization. SIGMETRICS Perf. Eval. Rev. 40(1), 65–76 (2012). doi:10.1145/2318857.2254767

    Article  Google Scholar 

  37. Traynor, P., Lin, M., Ongtang, M., Rao, V., Jaeger, T., McDaniel, P., La Porta, T.: On cellular botnets: measuring the impact of malicious devices on a cellular network core. In: Proceedings of 16th ACM conference on Computer and Communications Security (CCS), Chicago, pp. 223–234 (2009). doi:10.1145/1653662.1653690

  38. Wang, Z., Qian, Z., Xu, Q., Mao, Z., Zhang, M.: An untold story of middleboxes in cellular networks. In: Proceedings of ACM SIGCOMM, Toronto, pp. 374–385 (2011). doi:10.1145/2018436.2018479

Download references

Acknowledgments

We thank Mihajlo Pavloski and Gokce Gorbil for the simulation results, and the EU FP7 project NEMESYS (Enhanced Network Security for Seamless Service Provisioning in the Smart Mobile Ecosystem), grant agreement no. 317888, for financial support.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Erol Gelenbe .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Cite this paper

Gelenbe, E., Abdelrahman, O.H. (2016). Countering Mobile Signaling Storms with Counters. In: Mandler, B., et al. Internet of Things. IoT Infrastructures. IoT360 2015. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 169. Springer, Cham. https://doi.org/10.1007/978-3-319-47063-4_18

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-47063-4_18

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47062-7

  • Online ISBN: 978-3-319-47063-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics