Skip to main content
Log in

Collusion attacks mitigation in internet of things: a fog based model

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

Collusion attacks are among the major security concerns nowadays due to the growth exposure in networks and communications. Internet of Things (IoT) environments are an attractive target for such type attacks. This paper discusses the problem of collusion attacks in IoT environments and how mobility of IoT devices increases the difficulty of detecting such types of attacks. It demonstrates how approaches used in detection collusion attacks in WSNs are not applicable in IoT environments. To this end, the paper introduces a model based on Fog Computing infrastructure to keep track of IoT devices and detect collusion attackers. The model uses fog computing layer for realtime monitoring and detection of collusion attacks in IoT environments. Moreover, the model uses a software defined systems layer to add a degree of flexibility for configuring Fog nodes to enable them to detect various types of collusion attacks. The paper provides algorithms, theorems, lemmas and mathematical proofs of the proposed model. Furthermore, the it highlights the possible overhead on fog nodes and network when applying the proposed model, and claims that fog layer infrastructure can provide the required resources for the scalability of the model. The experiments show how the proposed model can keep track of malicious nodes while moving from one cluster to other clusters in IoT environments in contrary to the models used in WSNs. Moreover, the experiments show that the proposed model can bear the computation overhead effectevilly, and reduces the power consumption of aggregator nodes in comparison to the models used in WSNs.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Alsmearat K, Al-Ayyoub M, Bani Yassein M (2014) A new broadcast scheme for sensor networks. In: 2014 IEEE/ACS 11th international conference on computer systems and applications (AICCSA). IEEE, pp 824–828

  2. Alsmirat M, Jararweh Y, Obeidat I, Gupta B (2016) Internet of surveillance: a cloud supported large-scale wireless surveillance system. J Supercomput 1–20

  3. Amin R, Islam H, Vijayakumar P, Khan MK, Chang V (2017) A robust and efficient bilinear pairing based mutual authentication and session key verification over insecure communication. J Multimed Tools Appl 1–15

  4. Atzori L, Iera A, Morabito G (2010) The internet of things: a survey. Comput Netw 54(15):2787–2805

    Article  MATH  Google Scholar 

  5. Ayday E, Lee H, Fekri F (2009) An iterative algorithm for trust and reputation management. In: 2009 IEEE International symposium on information theory. IEEE, pp 2051–2055

  6. Calheiros RN, Ranjan R, Beloglazov A, De Rose CA, Buyya R (2011) Cloudsim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms. Softw Pract Exper 41(1):23–50

    Article  Google Scholar 

  7. Chen B-C, Guo J, Tseng B, Yang J (2011) User reputation in a comment rating environment. In: Proceedings of the 17th ACM SIGKDD international conference on knowledge discovery and data mining. ACM, pp 159–167

  8. De Kerchove C, Van Dooren P (2010) Mirai and iot botnet analysis. SIAM J Matrix Anal Appl 31(4):1812–1834

    Article  Google Scholar 

  9. Ganeriwal S, Balzano LK, Srivastava MB (2008) Reputation-based framework for high integrity sensor networks. ACM Trans Sensor Netw (TOSN) 4(3):15

    Google Scholar 

  10. Graham R (2017) Mirai and iot botnet analysis. In: RSA Conference 2017 RSA

  11. Jararweh Y, Doulat A, AlQudah O, Al-Ayyoub M, Benkhelifa E (2016) The future of mobile cloud computing: integrating cloudlets and mobile edge computing. In: Proceedings of the 23rd international conference on telecommunications (ICT). IEEE, pp 1–5

  12. Jararweh Y, Doulat A, Darabseh A, Alsmira M, Al-Ayyoub M, Benkhelifa E (2016) Sdmec: software defined system for mobile edge computing. In: Proceedings of the 2016 IEEE International workshop on cloud engineering (IC2EW). IEEE, pp 88–93

  13. Jing Q, Vasilakos A V, Wan J, Lu J, Qiu D (2014) Security of the internet of things: perspectives and challenges. Wirel Netw 20(8):2481–2501

    Article  Google Scholar 

  14. Laureti P, Moret L, Zhang Y-C, Yu Y-K (2006) Information filtering via iterative refinement. EPL (Europhys Lett) 75(6):1006

    Article  MathSciNet  Google Scholar 

  15. Li R-H, Yu J X, Huang X, Cheng H (2012) Robust reputation-based ranking on bipartite rating networks. In: SDM, vol 12. SIAM, pp 612–623

  16. Rezvani M, Ignjatovic A, Bertino E, Jha S (2013) A robust iterative filtering technique for wireless sensor networks in the presence of malicious attacks. In: Proceedings of the 11th ACM conference on embedded networked sensor systems. ACM, p 30

  17. Rezvani M, Ignjatovic A, Bertino E, Jha S (2015) Secure data aggregation technique for wireless sensor networks in the presence of collusion attacks. IEEE Trans Depend Secur Comput 12(1):98–110

    Article  Google Scholar 

  18. Tang L-A, Yu X, Kim S, Han J, Hung C-C, Peng W-C (2010) Tru-alarm: trustworthiness analysis of sensor networks in cyber-physical systems. In: 2010 IEEE International conference on data mining. IEEE, pp 1079–1084

  19. Vijayakumar P, Chang V, Deborah L, Balusamy B, Shynu PG (2017) Computationally efficient privacy preserving anonymous mutual and batch authentication schemes for vehicular ad hoc networks. J Fut Gen Comput Syst

  20. Whitmore A, Agarwal A, Da Xu L (2015) The internet of things—a survey of topics and trends. Inf Syst Front 17(2):261–274

    Article  Google Scholar 

  21. Wu R, Zhang B, Hsu M (2009) Clustering billions of data points using gpus. In: Proceedings of the combined workshops on UnConventional high performance computing workshop plus memory access workshop. ACM, pp 1–6

  22. Yang Y, Zheng X, Liu X, Zhong S, Chang V (2017) Cross-domain dynamic anonymous authenticated group key management with symptom-matching for e-health social system. J Fut Gen Comput Syst

  23. Yang Y, Zheng X, Chang V, Tang SY (2017) Lattice assumption based fuzzy information retrieval scheme support multi-user for secure multimedia cloud. J Multimed Tools Appl 1–15

  24. Yaseen Q, AlBalas F, Jararweh Y, Al-Ayyoub M (2016) A fog computing based system for selective forwarding detection in mobile wireless sensor networks. In: Foundations and applications of self* systems

  25. Yaseen Q, Jararweh Y, Al-Ayyoub M, AlDwairi M (2017) Collusion attacks in internet of things: detection and mitigation using a fog based model. In: Proceedings of the 2017 IEEE sensors applications symposium (SAS). IEEE, pp 23–50

  26. Yu Y-K, Zhang Y-C, Laureti P, Moret L (2006) Decoding information from noisy, redundant, and intentionally distorted sources. Physica Stat Mech Appl 371(2):732–744

    Article  Google Scholar 

  27. Zhou Y-B, Lei T, Zhou T (2011) A robust ranking algorithm to spamming. EPL (Europhys Lett) 94(4):48002

    Article  Google Scholar 

Download references

Acknowledgment

This work was supported in part by Zayed University Research Office, Research Cluster Award # R17079.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yaser Jararweh.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yaseen, Q., Aldwairi, M., Jararweh, Y. et al. Collusion attacks mitigation in internet of things: a fog based model. Multimed Tools Appl 77, 18249–18268 (2018). https://doi.org/10.1007/s11042-017-5288-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-017-5288-3

Keywords

Navigation