A remote attestation mechanism for the sensing layer nodes of the Internet of Things

Gong, Bei; Zhang, Yu; Wang, Yübo

doi:10.1016/j.future.2017.07.034

Cited by 40 publications

(15 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Authors in [15] proposed a remote validation mechanism to identify the node trust and to monitor their behaviour in real time environments. The problem identified by the researchers is that, most of the remote authentication mechanisms deployed in the perception layer are not able to continuously validate the trust level of a node, and are unable to provide tracking of these sensing nodes.…”

Section: Related Workmentioning

confidence: 99%

A decentralized lightweight blockchain-based authentication mechanism for IoT systems

et al. 2020

View full text Add to dashboard Cite

The Internet of Things (IoT) is an emerging paradigm branded by heterogeneous technologies composed of smart ubiquitous objects that are seamlessly connected to the Internet. These objects are often deployed in open environments to provide innovative services in various application domains such as smart cities, smart health, and smart communities. These IoT devices produce a massive amount of confidentiality and security-sensitive data. Thus, security of these devices is very important in order to ensure the safety and effectiveness of the system. In this paper, a decentralized authentication and access control mechanism is proposed for lightweight IoT devices and is applicable to a large number of scenarios. The mechanism is based on the technology of the fog computing and the concept of the public blockchain. The results gained from the experiments demonstrate a superior performance of the proposed mechanism when compared to a state-of-the-art blockchainbased authentication technique.

show abstract

Section: Related Workmentioning

confidence: 99%

A decentralized lightweight blockchain-based authentication mechanism for IoT systems

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Concepts of QoS are used for example in [13]: authors present a remote attestation mechanism for the sensing layer node in the IoT. A real-time trust measurement is realized through a combination of QoS factors, such as transmission delay, historical data and feedback originated from other objects.…”

Section: B Trustworthiness Modelsmentioning

confidence: 99%

Trust-Related Attacks and Their Detection: A Trust Management Model for the Social IoT

Marche

Nitti

2021

IEEE Trans. Netw. Serv. Manage.

View full text Add to dashboard Cite

The integration of social networking concepts into the Internet of Things (IoT) has led to the so called Social Internet of Things paradigm, according to which the objects are capable of establishing social relationships in an autonomous way with respect to their owners. Within this scenario, "things" interact opportunistically with their peers to seek needed services. However, attacks and malfunctions in the IoT can outweigh any of its benefits if not handled adequately. In this paper, we focus on the possible types of trust attacks that can affect the IoT and propose a trust management model able to overcome all the analyzed attacks. Simulations show how the proposed model can effectively isolate almost any malicious nodes in the network at the expense of an increase in the number of transactions needed for the model to converge.

show abstract

“…Although only 20% of access control methods currently use trust assessments, according to the researchers of [ 75 ], it is still a promising security mechanism because of its ability to calculate node dynamic trust value. The process helps the trust rating of each node to be measured gradually.…”

Section: Taxonomy Of Ml-based Aa For Iotmentioning

confidence: 99%

Machine Learning for Authentication and Authorization in IoT: Taxonomy, Challenges and Future Research Direction

Ahmed

Tahir

Habaebi

et al. 2021

Sensors

View full text Add to dashboard Cite

With the ongoing efforts for widespread Internet of Things (IoT) adoption, one of the key factors hindering the wide acceptance of IoT is security. Securing IoT networks such as the electric power grid or water supply systems has emerged as a major national and global priority. To address the security issue of IoT, several studies are being carried out that involve the use of, but are not limited to, blockchain, artificial intelligence, and edge/fog computing. Authentication and authorization are crucial aspects of the CIA triad to protect the network from malicious parties. However, existing authorization and authentication schemes are not sufficient for handling security, due to the scale of the IoT networks and the resource-constrained nature of devices. In order to overcome challenges due to various constraints of IoT networks, there is a significant interest in using machine learning techniques to assist in the authentication and authorization process for IoT. In this paper, recent advances in authentication and authorization techniques for IoT networks are reviewed. Based on the review, we present a taxonomy of authentication and authorization schemes in IoT focusing on machine learning-based schemes. Using the presented taxonomy, a thorough analysis is provided of the authentication and authorization (AA) security threats and challenges for IoT. Furthermore, various criteria to achieve a high degree of AA resiliency in IoT implementations to enhance IoT security are evaluated. Lastly, a detailed discussion on open issues, challenges, and future research directions is presented for enabling secure communication among IoT nodes.

show abstract

A remote attestation mechanism for the sensing layer nodes of the Internet of Things

Cited by 40 publications

References 30 publications

A decentralized lightweight blockchain-based authentication mechanism for IoT systems

A decentralized lightweight blockchain-based authentication mechanism for IoT systems

Trust-Related Attacks and Their Detection: A Trust Management Model for the Social IoT

Machine Learning for Authentication and Authorization in IoT: Taxonomy, Challenges and Future Research Direction

Contact Info

Product

Resources

About