A Survey on Blockchain-based Intrusion Detection Systems for IoT
DOI:
https://doi.org/10.21015/vtcs.v11i1.1385Abstract
The Internet of Things (IoT) is a contemporary concept that unifies the Internet and physical objects across various domains, such as home automation, manufacturing, healthcare, and environmental monitoring. This integration enables users to leverage Internet-connected devices in their daily routines. Despite its numerous advantages, IoT also presents several security challenges. As the popularity of IoT continues to grow, ensuring the security of IoT networks has become a critical concern. While encryption and authentication can enhance the security of IoT networks, protecting IoT devices against cyber-attacks remains a complex task. A successful cyber-attack on an IoT system may not only result in information loss but also potentially cripple the entire system. Intrusion detection systems (IDS) are instrumental in identifying malicious activities that could compromise or disrupt network performance. Consequently, there is a pressing need for effective IDS solutions to safeguard IoT systems. Blockchain, an emerging technology, bolsters security systems to counter modern threats. In this paper, we provide an extensive review of state-of-the-art blockchain-based intrusion detection systems for IoT applications. Additionally, we present recent advancements in addressing security concerns in a tabular format. Lastly, we identify open challenges and current limitations that warrant further exploration.
References
Shanzhi Chen, Hui Xu, Dake Liu, Bo Hu, Hucheng Wang,” A Vision of IoT: Applications, Challenges, and Opportunities with China Perspective”, IEEE Internet of Things Journal, Vol. 1, No. 4, August 2014.
Benabdessalem1, Mohamed Hamdi1, Tai-Hoon Kim2,”A Survey on Security Models, Techniques, and Tools for the Internet of Things”, 7th International Conference on Advanced Software Engineering Its Applications, 2014.
Shancang Li, Li Da Xu, Shanshan Zhao, ”The internet of things: a survey”, Springer Information Systems Frontiers, Volume 17, Issue 2, pp 243-259, April 2015.
P. Gokul Sai Sreeram, Chandra Mohan Reddy Sivappagari,” Development of Industrial Intrusion Detection and Moni- toring Using Internet of Things”, International Journal of Technical Research and Applications, 2015.
E. Borgia, The Internet of Things vision: Key features, applications and open issues, Computer Communications 54 (2014) 1–31.
M. Patel and A. Aggarwal,” Security attacks in wireless sensor networks: A survey”, 2013 International Conference on Intelligent Systems and Signal Processing (ISSP), 2013.
L. Clemmer, Information Security Concepts: Authenticity.
http://www.brighthub.com/computing/smb- security/articles/31234.aspx.A
Shyam Nandan Kumar,”Review on Network Security and Cryptography”, International Transaction of Electrical and Computer Engineers System, vol. 3, no. 1, pp. 1-11, 2015.
Mrs. V. Umadevi Chezhian, Dr. Ramar2, Mr.Zaheer Uddin Khan, ”Security Requirements in Mobile Ad Hoc Networks”, International Journal of Advanced Research in Computer and Communication Engineering, vol. 1, no. 2, pp. 45-49, 2012.
M. Hossain, M. Fotouhi and R. Hasan,” Towards an Analysis of Security Issues, Challenges, and Open Problems in the Internet of Things”, 2015 IEEE World Congress on Services, 2015.
Nabil Ali Alrajeh, S. Khan, and Bilal Shams,” Intrusion Detection Systems in Wireless Sensor Networks: A Review”, International Journal of Distributed Sensor Networks, vol. 2013, Article ID 167575, 7 pages, 2013.
Xiaolin Jia, Quanyuan Feng, Taihua Fan, Quanshui Lei, ”RFID technology and its applications in Internet of Things (IoT)”, 2nd International Conference on Consumer Electron- ics, Communications and Networks (CECNet), IEEE DOI: 10.1109/CECNet.2012.6201508, 2012.
Qi Jing, Athanasios V. Vasilakos, Jiafu Wan, Jingwei Lu, Dechao Qiu, ”Security of the Internet of Things: perspectives and challenges”, Published in Springer journal of Mobile Communication, Computation and Information, November 2014, Volume 20, Issue 8, pp 2481-2501.
Okan CAN, Ozgur Koray SAHINGOZ,”A Survey of Intrusion Detection Systems in Wireless Sensor Networks”, 6th International Conference on Modeling, Simulation, and Applied Optimization (ICMSAO), 2015.
Abdur Rahaman Sardar, Rashmi Ranjan Sahoo, Moutushi Singh, Souvik Sarkar, Jamuna Kanta Singh, and Koushik Ma- jumder, ”Intelligent Intrusion Detection System in Wireless Sensor Network”, Proc. Of the 3rd Int. Conf. on Front. Of Intell. Comput. (FICTA), 2014 Vol. 2, Advances in Intelligent Systems and Computing 328, Springer DOI: 10.1007/978-3- 319-12012-6 78.
J.Vacca, Computer and information security handbook, Morgan Kaufmann, Amsterdam, 2013.
A. Patel, Q. Qassim, C. Wills, A survey of intrusion detection and prevention systems, Information Management & Computer Security 18 (4) (2010) 277–290.
Zegzhda, P.; Kort, S. Host-Based Intrusion Detection System: Model and Design Features. In Proceedings of the International Conference on Mathematical Methods, Models, and Architectures for Computer Network Security, St. Petersburg, Russia, 13–15 September 2007; pp. 340–345. 16.
S. S. Chakravarthi and S. Veluru, “A review on intrusion detection techniques and intrusion detection systems in MANETs,” Proc. - 2014 6th Int. Conf. Comput. Intell. Commun. Networks, CICN 2014, pp. 730–737, 2014, doi: 10.1109/CICN.2014.159.
Li, Z. Cai, L. Deng, X. Yao, and H. H. Wang, “Information security model of block chain based on intrusion sensing in the IoT environment,” Cluster Comput., vol. 22, pp. 451–468, 2019, doi: 10.1007/s10586-018-2516-1.
C. Liang et al., “Intrusion detection system for the internet of things based on blockchain and multi-agent systems,” Electron., vol. 9, no. 7, pp. 1–27, 2020, doi: 10.3390/electronics9071120.
N. Ambili and Jimmy Jose, “Trust Based Intrusion Detection System to Detect Insider Attacks in IoT Systems,” Lect. Notes Electr. Eng., vol. 621, pp. 631–638, 2020, doi: 10.1007/978-981-15-1465-4_62.
F. I. Conference and R. S. Papers, Big Data , Machine Learning , and Applications. 2019.
W. Li, S. Tug, W. Meng, and Y. Wang, “Designing collaborative blockchained signature-based intrusion detection in IoT environments,” Futur. Gener. Comput. Syst., vol. 96, pp. 481–489, 2019, doi: 10.1016/j.future.2019.02.064.
Chen, Y., Liu, J.: Distributed community detection over blockchain networks based on structural entropy. In: Proceedings of the 2019 ACM International Symposium on Blockchain and Secure Critical Infrastructure—BSCI 19 (2019).
Kim, S., Kim, B., Kim, H.J.: Intrusion detection and mitigation system using blockchain analysis for bitcoin exchange. In: Proceedings of the 2018 International Conference on Cloud Computing and Internet of Things—CCIOT 2018 (2018).
G. D. Putra, V. Dedeoglu, S. S. Kanhere, and R. Jurdak, “Poster abstract: Towards scalable and trustworthy decentralized collaborative intrusion detection system for IoT,” Proc. - 5th ACM/IEEE Conf. Internet Things Des. Implementation, IoTDI 2020, pp. 256–257, 2020, doi: 10.1109/IoTDI49375.2020.00035.
Laufenberg, D., Li, L., Shahriar, H., Han, M.: An architecture for blockchain-enabled collaborative signature-based intrusion detection system. In: Proceedings of the 20th Annual SIG Conference on Information Technology Education—SIGITE 19 (2019).
N. Alexopoulos, E. Vasilomanolakis, N. R. Ivanko, and M. Muhlhauser, ‘‘Towards blockchain-based collaborative intrusion detection systems,’’ in Proc. Int. Conf. Critical Inf. Infrastruct. Secur., 2017, pp. 1–12.
B. Hu, C. Zhou, Y. C. Tian, Y. Qin, and X. Junping, “A Collaborative Intrusion Detection Approach Using Blockchain for Multimicrogrid Systems,” IEEE Trans. Syst. Man, Cybern. Syst., vol. 49, no. 8, pp. 1720–1730, 2019, doi: 10.1109/TSMC.2019.2911548.
Salman, T., Zolanvari, M., Erbad, A., Jain, R., Samaka, M.: Security services using blockchains: a state of the art survey. IEEE Commun. Surv. Tutor. 21(1), 850–880 (2019).
W. Meng, E. W. Tischhauser, Q. Wang, Y. Wang, and J. Han, “When intrusion detection meets blockchain technology: A review,” IEEE Access, vol. 6, pp. 10179–10188, 2018, doi: 10.1109/ACCESS.2018.2799854.
J.Vacca, Computer and information security handbook, Morgan Kaufmann, Amsterdam, 2013.
H.-J. Liao, C.-H. R. Lin, Y.-C. Lin, K.-Y. Tung, Intrusion detection system: A comprehensive review, Journal of Network and Computer Applications 36 (1) (2013) 16 – 24.
Chen Jun, Chen Chi,” Design of Complex Event-Processing IDS in Internet of Things”, Sixth International Conference on Measuring Technology and Mechatronics Automation, IEEE DOI: 10.1109/ICMTMA.2014.57, 2014.
Samir Athmani, Djallel Eddine Boubiche and Azeddine Bilami, ”Hierarchical Energy Efficient Intrusion Detection System for Black Hole Attacks in WSNs”, Published in Computer and Information Technology (WCCIT), 2013.
R. Mitchell, I.-R. Chen, A survey of intrusion detection techniques for CyberPhysical Systems, ACM Computing Surveys (CSUR) 46 (4) (2014) 55.
J.Amaral, L.Oliveira , J.Rodrigues, G.Han, L.Shu, Policy and network-based intrusion detection system for IPv6-enabled wireless sensor networks, in: Communications (ICC), 2014 IEEE International Conference on, 2014, pp. 1796–1801.
I. Butun, S. Morgera, R. Sankar, A survey of intrusion detection systems in wireless sensor networks, Communications Surveys Tutorials, IEEE 16 (1) (2014) 266–282.
P. T. Pham and S. Lee. (2017). ‘‘Anomaly detection in the bitcoin system—A network perspective.’’ [Online]. Available: https://arxiv.org/ abs/1611.03942.
W. Meng, W. Li, and L.-F. Kwok, ‘‘EFM: Enhancing the performance of signature-based network intrusion detection systems using enhanced filter mechanism,’’ Comput. Secur., vol. 43, pp. 189–204, Jun. 2014.
E.Ben-Sassonetal.,‘‘Zerocash: Decentralized anonymous payments from bitcoin,’’ in Proc. IEEE Symp. Secur. Privacy (SP), Berkeley, CA, USA, May 2014, pp. 459–474.
J. Yli-Huumo, D. Ko, S. Choi, S. Park, and K. Smolander, ‘‘Where is current research on blockchain technology?—A systematic review,’’PLoS ONE, vol. 11, no. 10, p. e0163477, 2016.
B. B. Zarpelão, R. S. Miani, C. T. Kawakani, and S. C. de Alvarenga, “A survey of intrusion detection in Internet of Things,” J. Netw. Comput. Appl., vol. 84, pp. 25–37, 2017, doi: 10.1016/j.jnca.2017.02.009.
M. A. Ferrag, L. Maglaras, A. Ahmim, M. Derdour, and H. Janicke, “RDTIDS: Rules and decision tree-based intrusion detection system for internet-of-things networks,” Futur. Internet, vol. 12, no. 3, pp. 1–14, 2020, doi: 10.3390/fi12030044.
Downloads
Published
How to Cite
Issue
Section
License
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC-By) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
This work is licensed under a Creative Commons Attribution License CC BY