Trust Management Framework for Internet of Things

Ruan, Yefeng; Durresi, Arjan; Alfantoukh, Lina

doi:10.1109/aina.2016.136

Cited by 41 publications

(20 citation statements)

References 23 publications

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“…Some proposals have also been set out regarding the modeling of the social and cooperative component. Among the most relevant of these are the works of Ruan et al 82 and Schatten et al 21 (third item of Table 4). On the one hand, Ruan et al propose a framework aimed at managing each agent’s level of confidence in order to help it assess the reliability of its counterparts.…”

Section: Resultsmentioning

confidence: 99%

Agentification of the Internet of Things: A systematic literature review

Pico-Valencia

Holgado-Terriza

2018

International Journal of Distributed Sensor Networks

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The Internet of Things is aimed at controlling the physical real world using a global network of heterogeneous smart objects that are interconnected through the Internet. Nonetheless, this emergent paradigm still poses challenges in terms of intelligence, autonomy, security, privacy, and interoperability, all of which must be overcome in order for this approach to be consolidated. The integration of Internet of Things with agent technologies has been proposed as an alternative. In this article, we present a general overview of the main preliminary models, theoretical and experimental studies, and applications currently proposed to carry out the agentification of the Internet of Things through modeling smart objects and networks of Internet of Things objects using software agents. Furthermore, we present an analysis of the main strengths, opportunities, weaknesses, and threats of this approach in terms of computational intelligence. Finally, we discuss the main challenges that must be overcome in order for the agentification process of the Internet of Things to become a consolidated paradigm to build cognitive Internet of Things applications.

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Section: Resultsmentioning

confidence: 99%

Agentification of the Internet of Things: A systematic literature review

Pico-Valencia

Holgado-Terriza

2018

International Journal of Distributed Sensor Networks

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“…Nevertheless, the major issue with this model is the irrelevance of trust score to the context as it focused on user contentment practices. In [26], the authors proposed a trust model based on social similarity. Trust is computed based on social similarity for indirect trust aggregation.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In this case, a total of 14 nodes out of 50 nodes are identified as malicious nodes as seen in the Figure 11. Node 1,2,5,9,10,24,25,26,32,34,35,38, and 39 are identified as malevolent nodes.…”

Section: Scenario-iimentioning

confidence: 99%

Dynamic distributed trust management scheme for the Internet of Things

Hamdani¹,

Khan²,

Iltaf³

et al. 2021

Turk J Elec Eng & Comp Sci

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The Internet of Things (IoT) comprises of a diverse network of homogeneous and heterogeneous nodes that can be accessed through network ubiquitously. In unattended environments, the IoT devices are prone to various attacks including ballot-stuffing, bad-mouthing, self-promotion, on-off, opportunistic behavior attacks, etc. The on-off attack is difficult to detect as nodes switch their behavior from normal to malicious alternatively. A trust management model is a tool to defend the IoT system against malicious activities and provide reliable data exchange. The majority of existing IoT trust management techniques are based on static reward and punishment values in pursuit of trust computation thereby allowing the misbehaving nodes to deliberately perform on-off attacks. Due to the static nature of awarding scores, these schemes fail to identify malicious nodes in certain cases. In this paper, a dynamic and distributed trust management scheme (DDTMS) is proposed where nodes can autonomously evaluate peer nodes' behavior and dynamically grant reward and penalty score. The proposed scheme successfully detects the on-off attack and isolates the misbehaving nodes thereby classifying them into three distinct categories based on their severity levels i.e. low, mild, and severe. Simulation-based performance evaluation shows improved performance of the proposed DDTMS against other state-of-the-art schemes thereby requiring less time and fewer interactions for successfully identifying malevolent behavior of compromised nodes.

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“…Ruan et al (Ruan et al,2016) introduces a general trust management framework aiming to help agents to evaluate their partners' trustworthiness.…”

Section: Research Articlementioning

confidence: 99%

Scalable Trust Management model for Machine To Machine communication in Internet of Things using Fuzzy approach

Railkar¹

2021

TURCOMAT

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Revolution in Machine to Machine (M2M) Communication in Internet of Things (IoT) provides smart services in all verticals. These smart heterogeneous devices can be constraint or powerful devices that are generating sensitive information and introducing new challenges in security, privacy, and trust in devices to get and provide services in a distributed fashion. These challenges are overcome by providing scalable decentralized trust management for the access control system. Trust-based security models are more reliable over cryptographic security to identify and mitigate different inside threats by assessing the trust scores. This paper proposed Scalable Trust Management (STM) using a fuzzy approach and parameters like Experience, Recommendation, and device classification are used to calculate the crisp value of the trust score. While designing rule for trust score capacity of device is considered. The simulation of STM in NS2 ensures good performance and its result guarantees scalability and energy efficiency in the heterogeneous network.

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Trust Management Framework for Internet of Things

Cited by 41 publications

References 23 publications

Agentification of the Internet of Things: A systematic literature review

Agentification of the Internet of Things: A systematic literature review

Dynamic distributed trust management scheme for the Internet of Things

Scalable Trust Management model for Machine To Machine communication in Internet of Things using Fuzzy approach

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