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Trust Authorization Monitoring Model in IoT

Volume 14, Number 3, March 2018, pp. 453-462
DOI: 10.23940/ijpe.18.03.p6.453462

Ruizhong Dua,b, Chong Liua,b, and Fanming Liua,b

aCyberspace Security and Computer College, Baoding, 071002, China
bKey Laboratory on High Trusted Information System in Hebei Province, Baoding, 071002, China

(Submitted on December 23, 2017; Revised on January 27, 2018; Accepted on February 24, 2018)


Abstract:

With strong heterogeneity and the limited computing ability of IoT nodes, this dissertation proposes a Trust Authorization Model based on detection feedback in IoT that is combined with the current trust model of IoT as well as implement storage and other tasks. By calculating and storing the cluster head node along with its strong ability to facilitate the data transmission and search for energy consumption, it prevents the local network from being limited by the computing power of the device. In terms of trust calculation, the threshold value is based on the recommendation. At the same time, the BP neural network algorithm with self-learning function is periodically detecting the interactive data stream, detecting the attack nodes, quickly implementing the response measures, and meeting the actual situation of unmanned IoT of mass devices. Simulation results show that this model has lower energy consumption than other similar models, has good coping ability for attacks such as malicious recommendation and malicious slander, and has a higher detection rate and response rate to attack nodes.

 

References: 15

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  8. W. M. Liu, L. H. Yin, B. X. Fang and so on.” Study on the Trust Mechanism Under the Internet of Things” [J]. Chinese Journal of Computers, 2012,35 (5): 847-855.
  9. Y. B. Liu, W. P. Hu “Internet of Things Security Model and Key Technologies” [J]. Digital Communications, 010, 37 (4): 28-33,2010.
  10. M. Nitti, R. Girau, and L. Atzori, “Trustworthiness Management in the Social Internet of Things,” IEEE Trans. Knowl. Data Eng., vol. 26, no. 5, pp. 1253–1266, 2014.
  11. ROMANA. R, ZHOUA. J, LOPEZB. J. “On the Features and Challenges of Security & Privacy in Distributed Internet of Things” [J]. Computer Networks, 2013, 57 (10):2266-2279.
  12. Srinivas Mukkamala, Andrew H. Sung. “Identifying Significant Features for Network Forensic Analysis Using Artificial Intelligent Techniques” [J], International Journal of Digital Evidence, Winter 2003,4:63-69.
  13. H. Xu. “Research on the Trust Model of Internet of Things Based on Clustering” [D]. Lanzhou traffic University, 2017.
  14. J. You, Shangguan Lun, Xu Shoukun, et al. “A Distributed Dynamic Trust Management Model Considering Trust Reliability” [J]. Journal of Software, 2017.
  15. A. K. Zeeshan, H. Peter, “A Trust Based Distributed Intrusion Detection Mechanism for Internet of Things”, In 2017 IEEE 31st International Conference on Advanced Information Networking and Applications. IEEE, 2017, pp.1169-1176

 

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