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An Experimental Study of Distributed Denial of Service and Sink Hole Attacks on IoT based Healthcare Applications

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Abstract

With the rapid growth of the Internet-of-Things (IoT) in healthcare and the challenging task of achieving communication between two devices working on different protocols, concerns about the security of its devices also become an essential aspect. Amelioration in healthcare infrastructure in developing economies increases cost-effective medical devices, high research and development investments by major medical companies, and growing IoT infrastructure in health care. Since the communication is wireless and consists of low latency-based sensors and actuators, they are susceptible to frequent attacks. Two of the most common attacks are the DDoS (Distributed Denial of service) and Sinkhole attack, which are discussed in context to AODV and RPL protocols, usually employed for wireless-based IoT healthcare applications. We present network models under such attacks and depict their impact on the network parameters, namely, throughput, delay and packet delivery ratio. Our article presents an experimental study on the impacts of DDoS and Sinkhole attacks and suggests detection strategies on the basis of channel congestion and energy consumption for an IoT-based healthcare network.

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References

  1. Mohapatro, M., & Snigdh, I. (2020). 11 Security in IoT. In S. K. Sharma, B. Bhushan, & N. C. Debnath (Eds.), IoT security paradigms and applications: Research and practices (p. 237). CRC Press.

    Chapter  Google Scholar 

  2. Butt, SA., Diaz-Martinez, J.L., Jamal, T., Ali, A., De-La-Hoz-Franco, E., Shoaib, M., (2019) IoT smart health security threats. In: 2019 19th international conference on computational science and its applications (ICCSA).

  3. Yuchen, Y., et al. (2017). A survey on security and privacy issues in Internet-of-things. IEEE Internet of Things Journal, 4(5), 1250–1258.

    Article  Google Scholar 

  4. Aggarwal, C. C., Ashish, N., & Sheth, A. (2013). The internet of things: A survey from the data-centric perspective. In C. C. Aggarwal (Ed.), Managing and mining sensor data (pp. 383–428). Springer.

    Chapter  Google Scholar 

  5. Catherwood, P. A., Steele, D., Little, M., Mccomb, S., & Mclaughlin, J. (2018). A community-based IoT personalized wireless healthcare solution trial. IEEE Journal of Translational Engineering in Health and Medicine, 6, 1–13.

    Article  Google Scholar 

  6. Wu, F., Taiyang, Wu., & Yuce, M. (2019). An internet-of-things (IoT) network system for connected safety and health monitoring applications. Sensors, 19(1), 21.

    Article  Google Scholar 

  7. Borgohain, T., U Kumar, and S Sanyal. (2015) Survey of security and privacy issues of internet of things. arXiv preprint.

  8. Kumar, J. S., & Patel, D. R. (2014). A survey on internet of things: Security and privacy issues. International Journal of Computer Applications, 90(11), 20–26.

    Article  Google Scholar 

  9. Bhargavi, M., & Rao, M. N. (2018). Security Issues and Challenges in IOT: A comprehensive study. International Journal of Engineering & Technology, 7, 298.

    Article  Google Scholar 

  10. Sahu, N. K., Patnaik, M., & Snigdh, I. (2021). Data analytics and its applications in brief. In S. Goundar & P. K. Rayani (Eds.), Applications of big data in large-and small-scale systems (pp. 115–125). IGI Global.

    Chapter  Google Scholar 

  11. Bhushan, B., & Sahoo, G. (2018). Recent advances in attacks, technical challenges, vulnerabilities and their countermeasures in wireless sensor networks. Wireless Personal Communications, 98(2), 2037–2077.

    Article  Google Scholar 

  12. Swamy, SN., Jadhav, D., and Kulkarni, N., (2017) Security threats in the application layer in IOT applications. In: 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC). IEEE.

  13. Roosta, T., Shieh, S., and Sastry, S., (2006) Taxonomy of security attacks in sensor networks and countermeasures. In: The first IEEE international conference on system integration and reliability improvements. Vol. 25.

  14. Osanaiye, O., Choo, K. K. R., & Dlodlo, M. (2016). Distributed denial of service (DDoS) resilience in cloud: Review and conceptual cloud DDoS mitigation framework. Journal of Network and Computer Applications, 67, 147–165.

    Article  Google Scholar 

  15. Bhushan, B., & Sahoo, G. (2020). ISFC-BLS (intelligent and secured fuzzy clustering algorithm using balanced load sub-cluster formation) in WSN environment. Wireless Personal Communications, 111(3), 1667–1694.

    Article  Google Scholar 

  16. Kenney, M. (2015). Cyber-terrorism in a post-stuxnet world. Orbis, 59(1), 111–128.

    Article  Google Scholar 

  17. Ahlawat, P., & Dave, M. (2018). An attack model based highly secure key management scheme for wireless sensor networks. Procedia Computer Science, 125, 201–207.

    Article  Google Scholar 

  18. Radlein, Anton Stephen, Nathan Alan Dye, Craig Wesley Howard, and HarvoReyzell Jones. (2018) Mitigating network attacks. U.S. Patent Application 15/714,993, filed April 19.

  19. Ramesh, C., et al. (2018) FPGA side channel attacks without physical access. In: 2018 IEEE 26th annual international symposium on field-programmable custom computing machines (FCCM), IEEE.

  20. Wu, J., Liao, X., & Yang, Bo. (2018). Cryptanalysis and enhancements of image encryption based on three-dimensional bit matrix permutation. Signal Processing, 142, 292–300.

    Article  Google Scholar 

  21. Kocher, P., et al. (2018) Spectre attacks: Exploiting speculative execution. arXiv preprint.

  22. Razzaq, M. A., et al. (2017). Security issues in the Internet of Things (IoT): A comprehensive study. International Journal of Advanced Computer Science and Applications, 8(6), 383.

    Google Scholar 

  23. Majumder, S., Mondal, T., & Deen, M. (2017). Wearable sensors for remote health monitoring. Sensors, 17(1), 130.

    Article  Google Scholar 

  24. Milenković, A., Otto, C., & Jovanov, E. (2006). Wireless sensor networks for personal health monitoring: Issues and an implementation. Computer Communications, 29(13–14), 2521–2533.

    Article  Google Scholar 

  25. Jovanov, E., et al. (2005). A wireless body area network of intelligent motion sensors for computer assisted physical rehabilitation. Journal of Neuro Engineering and Rehabilitation, 2(1), 1–10.

    Article  Google Scholar 

  26. Cha, H.-J., Yang, H.-K., & Song, Y.-J. (2018). A study on the design of fog computing architecture using sensor networks. Sensors, 18(11), 3633.

    Article  Google Scholar 

  27. Mistry, N., Jinwala, DC., and Zaveri, M., (2010) Improving AODV protocol against blackhole attacks. In: Proceedings of the international multi conference of engineers and computer scientists. Vol. 2.

  28. Gardner, MT., Beard, C., and Medhi, D., (2017) Using SEIRS epidemic models for IoT botnets attacks. In: 13th international conference DRCN 2017-design of reliable communication networks, VDE.

  29. Wallgren, L., Raza, S., & Voigt, T. (2013). Routing attacks and countermeasures in the RPL-based internet of things. International Journal of Distributed Sensor Networks, 9(8), 794326.

    Article  Google Scholar 

  30. Rai, A. K., Tewari, R. R., & Upadhyay, S. K. (2010). Different types of attacks on integrated MANET-Internet communication. International Journal of Computer Science and Security, 4(3), 265–274.

    Google Scholar 

  31. Verma, A., & Ranga, V. (2019). Evaluation of network intrusion detection systems for RPL based 6LoWPAN networks in IoT. Wireless Personal Communications, 108, 1–24.

    Article  Google Scholar 

  32. Zant, M. A., & Yasin, A. (2019). Avoiding and isolating flooding attack by enhancing AODV MANET protocol (AIF_AODV). Security and Communication Networks, 2019, 1–19.

    Article  Google Scholar 

  33. S. Alanazi, J. Al-Muhtadi, A. Derhab, K. Saleem, (2015) On resilience of wireless mesh routing protocol against DoS attacks in IoT-based ambient assisted living applications. In: international conference on e-health networking application & services.

  34. Srivastava, A., et al. (2011) A recent survey on DDoS attacks and defense mechanisms. In: International conference on parallel distributed computing technologies and applications. Springer, Berlin, Heidelberg.

  35. Broch, J., et al. (1998) A performance comparison of multi-hop wireless ad hoc network routing protocols. In: Proceedings of the 4th annual ACM/IEEE international conference on mobile computing and networking.

  36. Wallgren, L., Raza, S., & Voigt, T. (2013). Routing attacks and countermeasures in the RPL-based internet of things. International Journal of Distributed Sensor Networks, 9(8), 794326.

    Article  Google Scholar 

  37. Manorama M., I Snigdh (2018) Anonymity in body area sensor networks-an insight. In: 2018 IEEE world symposium on communication engineering (WSCE).

  38. Rghiout, A., Khannous, A., & Bouhorma, M. (2014). Denial-of-service attacks on 6lowpan-RPL networks: Issues and practical solutions. Journal of Advanced Computer Science & Technology, 3(2), 143–153.

    Article  Google Scholar 

  39. Sundararajan, R. K., & Arumugam, U. (2015). Intrusion detection algorithm for mitigating sinkhole attack on LEACH protocol in wireless sensor networks. Journal of Sensors, 2015, 1–12.

    Article  Google Scholar 

  40. Ansam, K., & Alazab, A. (2021). A critical review of intrusion detection systems in the internet of things: Techniques, deployment strategy, validation strategy, attacks, public datasets and challenges. Cybersecurity. https://doi.org/10.1186/s42400-021-00077-7

    Article  Google Scholar 

  41. Nagireddy, V., & Parwekar, P. (2019). Attacks in wireless sensor networks. In S. C. Satapathy, V. Bhateja, & S. Das (Eds.), Smart intelligent computing and applications (pp. 439–447). Springer.

    Chapter  Google Scholar 

  42. Kamgueu, P. O., Nataf, E., & Ndie, T. D. (2018). Survey on RPL enhancements: A focus on topology, security and mobility. Computer Communications, 120, 10–21.

    Article  Google Scholar 

  43. Alzubaidi, M., et al. (2017) Review on mechanisms for detecting sinkhole attacks on RPLs. In: 2017 8th International Conference on Information Technology (ICIT). IEEE.

  44. Jebadurai, I. J. R., et al. (2016). EDIS: an effective method for detection and isolation of sinkhole attacks in mobile ad hoc networks. International Journal of Wireless and Mobile Computing, 11(3), 171–181.

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Birla Institute of Technology, Mesra, Jharkhand, 835001, India

    Manorama Mohapatro & Itu Snigdh

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  1. Manorama Mohapatro
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Correspondence to Manorama Mohapatro.

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Mohapatro, M., Snigdh, I. An Experimental Study of Distributed Denial of Service and Sink Hole Attacks on IoT based Healthcare Applications. Wireless Pers Commun 121, 707–724 (2021). https://doi.org/10.1007/s11277-021-08657-z

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