Effective distributed trust management model for Internet of Things

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Abstract

The IoT (Internet of Things) is defined as a global infrastructure for the information society, which provides advanced Services by interconnecting physical or virtual objects through existing interoperable information and communication technologies in evolution. To note, the explosion of the number of smartphones and connections has created a new market with almost infinite opportunitieS. In 2016, 5.5 million objects are connected every day in the world. A number that could quickly reach billions, by 2020 [1]. Gartner predicts that 26 billion objects will be installed in 2020. Other evaluations consider that a human being would interact with 1,000 to 5,000 objects during a normal day. The market for connected objects could range from a few tens of billions to up to several thousand billion unitS. Among the vital components of IoT, we find wireless sensor networkS. WsNs allow the representation of dynamic characteristics of the real world in the virtual world of the Internet. Nevertheless, the opening of these types of network to the Internet presents a serious problem stand point security. The introduction of intrusion detection mechanisms is essential to limit the various attacks that threaten the proper functioning of the networkS. In this work, we propose a new intrusion detection model for Internet of Things, specifically for WsNS. This model relies on a geographic location check of the nodes to make sure that we communicate with the right node for each transaction. subsequently, we proposed rules for detecting attackS. A mathematical model for trust calculating was proposed to update trust nodes values and eliminate malicious nodeS. The simulation results were able to show the effectiveness of our model.

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APA

Maddar, H., Kammoun, W., & Youssef, H. (2018). Effective distributed trust management model for Internet of Things. In Procedia Computer Science (Vol. 126, pp. 321–334). Elsevier B.V. https://doi.org/10.1016/j.procS.2018.07.266

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