Abstract
The Internet of Things (IoT) is a ubiquitous network formed on the basis of the traditional Internet. The sensor layer of IoT is the bridge between the world of information and the real world. The security of the sensor network of IoT is the primary basis for the credibility of the IoT. Only when the security of the sensor network is guaranteed, the security of IoT can be guaranteed. However, the existing security mechanism is mainly based on passive defense and cannot actively respond to many unknown security threats. Therefore, it is necessary to study an active immunity mechanism suitable for IoT sensor nodes. This article will mainly design an active immune mechanism that can meet the security requirements of IoT sensor nodes for the sensor layer of IoT, and combine the relevant feedback mechanism to adjust the credibility measurement policy between nodes in real time, so that the mechanism can be adjusted in real time according to environmental changes. In this way, it is more proactive to ensure the security of the sensor network. Simulation results show that the security strategy in this paper can better deal with the security threats brought by malicious nodes than the traditional strategy, and the response time is reduced by about 50%.
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References
Sedjelmaci, H., Senouci, S.M., Taleb, T.: An accurate security game for low-resource IoT devices. IEEE Trans. Veh. Technol. 66(10), 9381–9393 (2017)
Wang, J., Hong, Z., Zhang, Y., Jin, Y.: Enabling security-enhanced attestation with Intel SGX for remote terminal and IoT. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 37(1), 88–96 (2018)
Kim, M., Lee, N., Park, J.: A security generic service interface of Internet of Things (IoT) platforms. Symmetry 9(9), 171 (2017)
Mangia, M., Pareschi, F., Rovatti, R., Setti, G.: Low-cost security of IoT sensor nodes with rakeness-based Compressed sensing: statistical and known-plaintext attacks. IEEE Trans. Inf. Forensics Secur. 13(2), 327–340 (2018)
Nurse, J.R.C., Creese, S., Roure, D.D.: Security risk assessment in internet of things systems. IT Professional 19(5), 20–26 (2017)
Abeshu, A., Chilamkurti, N.: Deep learning: the frontier for distributed attack detection in fog-to-things computing. IEEE Commun. Mag. 10(2), 169–175 (2018)
Mahalle, P.N., Thakre, P.A., Prasad, N.R., Prasad, R.: A fuzzy approach to trust based access control in Internet of Things. In: Proceedings of the Wireless VITAE 2013, pp. 1–5. IEEE, Atlantic City (2013)
Abbas, R., Shirvanimoghaddam, M., Li, Y., Vucetic, B.: Random access for M2M communications with QoS guarantees. IEEE Trans. Commun. 65(7), 2889–2903 (2017)
Li, Y., Chai, K., Chen, Y., Loo, J.: Distributed access control framework for IPv6-based hierarchical Internet of Things. IEEE Wirel. Commun. 16(10), 17–23 (2016)
Chen, I., Bao, F., Guo, J.: Trust-based service management for social Internet of Things systems. IEEE Trans. Dependable Secure Comput. 13(6), 684–696 (2016)
Maene, P., Gotzfried, J., Clercq, R.D., Muller, T., Freiling, F.: Hardware-based trusted computing architectures for isolation and attestation. IEEE Trans. Comput. 99(1), 1–14 (2017)
Margheri, A., Masi, M., Pugliese, R., Tiezzi, F., Rigorous, A.: Framework for specification, analysis and enforcement of access control policies. IEEE Trans. Software Eng. 99(1), 1–58 (2016)
Hussein, D., Bertin, E., Frey, V.: A community-driven access control approach in distributed IoT environments. IEEE Commun. Mag. 50(3), 146–153 (2017)
MeenaKowshalyal, A., Valarmathi, M.L.: Trust management for reliable decision making among social objects in the social Internet of Things. IET Networks 6(4), 75–80 (2017)
Acknowledgement
This work is supported by State Grid Technical Project “Research on key technologies of secure and reliable slice access for Energy Internet services” (5204XQ190001). The authors declare that they have no conflicts of interest to report regarding the present study.
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Zhong, C., Lu, P., Guo, S., Kang, S. (2021). Adaptive Active Immune Policy for Sensor Nodes in Internet of Things. In: Sun, X., Zhang, X., Xia, Z., Bertino, E. (eds) Advances in Artificial Intelligence and Security. ICAIS 2021. Communications in Computer and Information Science, vol 1424. Springer, Cham. https://doi.org/10.1007/978-3-030-78621-2_43
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DOI: https://doi.org/10.1007/978-3-030-78621-2_43
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