Implementation and Evaluation of an Intrusion Detection System for IoT: Against Routing Attacks

  • Mohamed KhardiouiEmail author
  • Abdelouahed Bamou
  • My Driss El Ouadghiri
  • Badraddine Aghoutane
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 92)


The intensive growth of technology and devices connected to the Internet has made the Internet of Things (IoT) an essential element in all sectors of activity. It can be found in our watches, houses, cars, refrigerators, industrial machines, etc. Simply put, The Internet of Things is the future of technology that makes it easier to collect, analyze and distribute data that some person can implement them to achieve information or knowledge. Despite these advantages, this evolution suffers from a major security problem. This is due in particular to their heterogeneous nature, as well as the constraints of these objects (Memory, Processing Capabilities and limited energy…) are the main vulnerabilities of the IoT that are the origin of various attacks. Thus, many solutions have been developed to secure the IoT, but this remains insufficient because of the limitations of these mechanisms. This document is dedicated to the implementation and evaluation of an intrusion detection system (IDS) against attacks targeting the routing protocol in the IoT environment. The evaluation of the IDS is carried out with an emphasis on energy consumption, and detection rate. To achieve this, we have selected Cooja software as the simulator.


Security IoT Intrusion detection system IDS RPL Sinkhole 


  1. 1.
    Atzori, L., Iera, A., Morabito, G.: Understanding the Internet of Things: definition, potentials, and societal role of a fast evolving paradigm. Ad Hoc Netw. 56, 122–140 (2017). Scholar
  2. 2.
    Li, S., Tryfonas, T., Li, H.: The Internet of Things: a security point of view. Internet Res. 26, 337–359 (2016). Scholar
  3. 3.
    Khan, M.M., Lodhi, M.A., Rehman, A., Khan, A., Hussain, F.B.: Sink-to-sink coordination framework using RPL: routing protocol for low power and lossy networks. J. Sens. 2016, 1–11 (2016). Scholar
  4. 4.
    Ghosal, A., Halder, S.: A survey on energy efficient intrusion detection in wireless sensor networks. J. Ambient Intell. Smart Environ. 9, 239–261 (2017). Scholar
  5. 5.
    Wallgren, L., Raza, S., Voigt, T.: Routing attacks and countermeasures in the RPL-based Internet of Things. Int. J. Distrib. Sens. Netw. 9, 794326 (2013). Scholar
  6. 6.
    Stephen, R.: Deist: dynamic detection of Sinkhole attack for Internet of Things. Int. J. Eng. Comput. Sci. 5(12), 19358–19362 (2016). Research scholar Department of Computer Science St. Joseph’s College (Autonomous) Tiruchirappalli-620002CrossRefMathSciNetGoogle Scholar
  7. 7.
    Colom, J.F., Gil, D., Mora, H., Volckaert, B., Jimeno, A.M.: Scheduling framework for distributed intrusion detection systems over heterogeneous network architectures. J. Netw. Comput. Appl. 108, 76–86 (2018). Scholar
  8. 8.
    Clausen, T., Herberg, U., Philipp, M.: A critical evaluation of the IPv6 routing protocol for low power and lossy networks (RPL). In: 2011 IEEE 7th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), pp. 365–372. IEEE, Shanghai (2011)Google Scholar
  9. 9.
    Vucinic, M., Romaniello, G., Guelorget, L., Tourancheau, B., Rousseau, F., Alphand, O., Duda, A., Damon, L.: Topology construction in RPL networks over Beacon-enabled 802.15.4. ArXiv arXiv:1404.7803 Cs (2014)
  10. 10.
    Pu, C., Song, T.: Hatchetman attack: a denial of service attack against routing in low power and lossy networks. In: 2018 5th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/2018 4th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom), pp. 12–17. IEEE, Shanghai (2018)Google Scholar
  11. 11.
    Mayzaud, A., Badonnel, R., Chrisment, I.: A taxonomy of attacks in RPL-based Internet of Things. vol. 16 (2016) Google Scholar
  12. 12.
    Sundararajan, R.K., Arumugam, U.: Intrusion detection algorithm for mitigating sinkhole attack on LEACH protocol in wireless sensor networks. J. Sens. 2015, 1–12 (2015). Scholar
  13. 13.
    Ioulianou, P., Vasilakis, V., Moscholios, I., Logothetis, M.: A signature-based intrusion detection system for the Internet of Things. 7 (2018) Google Scholar
  14. 14.
    Nygaard, F.: Intrusion detection system in IoT. 125 (2017)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Mohamed Khardioui
    • 1
    Email author
  • Abdelouahed Bamou
    • 1
  • My Driss El Ouadghiri
    • 1
  • Badraddine Aghoutane
    • 2
  1. 1.IA Laboratory Science FacultyMoulay Ismail University of MeknesMeknesMorocco
  2. 2.TTI Team, Polydisciplinary Faculty of ErrachidiaMoulay Ismail University of MeknesMeknesMorocco

Personalised recommendations