T_CAFE: A Trust based Security approach for Opportunistic IoT

Kandhoul, Nisha; Dhurandher, Sanjay Kumar; Woungang, Isaac

doi:10.1049/iet-com.2019.0657

Cited by 25 publications

(12 citation statements)

References 22 publications

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“…Kandhoul et al 14 proposed RFCSec: a RF classifier for safe and reliable routing in opportunistic IoT (OppIoT) to associate humans with their own smart devices in opportunistic contact nature. The proposed protocol runs two principal phases.…”

Section: Ml‐based Solutions For Iotmentioning

confidence: 99%

“…The IoT is a networking architecture that provides pervasive distributed services as a step toward ubiquitous computing. The “IoT” is a network of physical items or things that use the Internet to share information and interact with one another and their surroundings 14 . The IoT enables the connection of millions of objects, including sensors and mobile phones/devices, to carry out numerous functions.…”

Section: Introductionmentioning

confidence: 99%

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A systematic literature review of machine learning applications in IoT

Gherbi

Senouci

Harbi

et al. 2023

Int J Communication

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The Internet of Things (IoT) is a network of interconnected smart objects having capabilities that collectively form an ecosystem and enable the delivery of smart services to users. The IoT is providing several benefits into people's lives through the environment. The various applications that are run in the IoT environment offer facilities and services. The most crucial services provided by IoT applications are quick decision for efficient management. Recently, machine learning (ML) techniques have been successfully used to maximize the potential of IoT systems. This paper presents a systematic review of the literature on the integration of ML methods in the IoT. The challenges of IoT systems are split into two categories: fundamental operation and performance. We also look at how ML is assisting in the resolution of fundamental system operation challenges such as security, big data, clustering, routing, and data aggregation.

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Section: Ml‐based Solutions For Iotmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A systematic literature review of machine learning applications in IoT

Gherbi

Senouci

Harbi

et al. 2023

Int J Communication

View full text Add to dashboard Cite

show abstract

“…Because of the difficulty in debugging and implementing IoTs in real networks, it is necessary to view simulations as a basic design tool. The primary benefit of simulation is that analysis is simplified and protocol is verified, mostly, it is evident in systems in large scales [28][29][30][31][32][33][34][35]. The performance of the suggested method is assessed in this part by the use of NS-3 as the simulation means, and the discussion on the obtained results is presented.…”

Section: Simulation Setup and Comparing Algorithmsmentioning

confidence: 99%

Multi-level trust-based intelligence schema for securing of internet of things (IoT) against security threats using cryptographic authentication

et al. 2020

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The Internet of Things (IoT) is able to provide a prediction of linked, universal, and smart nodes that have autonomous interaction when they present services. Because of wide openness, relatively high processing power, and wide distribution of IoT things, they are ideal for attacks of the gray hole. In the gray hole attack, the attacker fakes itself as the shortest path to the destination that is a thing here. This causes the routing packets don't reach the destination. The proposed method is based on the AODV routing protocol and is presented under the MTISS-IoT name which means for the reduction of gray hole attacks using check node information. In this paper, a hybrid approach is proposed based on cryptographic authentication. The proposed approach consists of four Phases, such as the verifying node trust in the IoT, testing the routes, gray hole attack discovery, and the malicious attack elimination process in MTISS-IoT. The method is evaluated here via extensive simulations carried out in the NS-3 environment. The experimental results of four scenarios demonstrated that the MTISS-IoT method can achieve a false-positive rate of 14.104 percent, a false-negative rate of 17.49 percent and a detection rate of 94.5 percent when gray hole attack was launched.

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“…IoT interplays between the paradigms of security and trust, i.e., if we regard security mechanisms in terms of barriers, locks, and accesses, then trust is a worry of when, where, and why to put these barriers, locks, and accesses in an IoT ecosystem to deal with the degree of collaboration and integration between the IoT objects [35]. Over the past decade, trust-based security mechanisms have emerged for enhancing the overall security of IoT, wherein trust and reputation models have been utilized to improve the collaboration and for selecting the trustworthy service provider based on quality-of-service (QoS), especially in service oriented architecture-based IoT [36], [37].…”

Section: Security Privacy and Trust In Iotmentioning

confidence: 99%

The 10 Research Topics in the Internet of Things

Zhang

Sheng

Mahmood

et al. 2020

Preprint

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Since the term first coined in 1999 by Kevin Ashton, the Internet of Things (IoT) has gained significant momentum as a technology to connect physical objects to the Internet and to facilitate machine-to-human and machine-to-machine communications. Over the past two decades, IoT has been an active area of research and development endeavors by many technical and commercial communities. Yet, IoT technology is still not mature and many issues need to be addressed. In this paper, we identify 10 key research topics and discuss the research problems and opportunities within these topics.

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T_CAFE: A Trust based Security approach for Opportunistic IoT

Cited by 25 publications

References 22 publications

A systematic literature review of machine learning applications in IoT

A systematic literature review of machine learning applications in IoT

Multi-level trust-based intelligence schema for securing of internet of things (IoT) against security threats using cryptographic authentication

The 10 Research Topics in the Internet of Things

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