An adaptive IoT trust estimation scheme combining interaction history and stereotypical reputation

Son, Heesuk; Kang, Namyong; Gwak, Bumjin; Lee, Dongman

doi:10.1109/ccnc.2017.7983132

Cited by 22 publications

(11 citation statements)

References 9 publications

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“…• Reputation-based: Reputation is a fundamental concept in several situations which can be involved in the interaction between mutually distrusting parties [240], [241]. Reputation-based trust relies on a "soft computational" approach to formulate the problem of trust.…”

Section: Property-basedmentioning

confidence: 99%

Security, Privacy and Trust for Smart Mobile- Internet of Things (M-IoT): A Survey

et al. 2020

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With an enormous range of applications, the Internet of Things (IoT) has magnetized industries and academicians from everywhere. IoT facilitates operations through ubiquitous connectivity by providing Internet access to all the devices with computing capabilities. With the evolution of wireless infrastructure, the focus from simple IoT has been shifted to smart, connected and mobile IoT (M-IoT) devices and platforms, which can enable low-complexity, low-cost and efficient computing through sensors, machines, and even crowdsourcing. All these devices can be grouped under a common term of M-IoT. Even though the positive impact on applications has been tremendous, security, privacy and trust are still the major concerns for such networks and insufficient enforcement of these requirements introduces non-negligible threats to M-IoT devices and platforms. Thus, it is important to understand the range of solutions which are available for providing a secure, privacy-compliant, and trustworthy mechanism for M-IoT. There is no direct survey available, which focuses on security, privacy, trust, secure protocols, physical layer security and handover protections in M-IoT. This paper covers such requisites and presents comparisons of statethe-art solutions for IoT which are applicable to security, privacy, and trust in smart and connected M-IoT networks. Apart from these, various challenges, applications, advantages, technologies, standards, open issues, and roadmap for security, privacy and trust are also discussed in this paper.

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Section: Property-basedmentioning

confidence: 99%

Security, Privacy and Trust for Smart Mobile- Internet of Things (M-IoT): A Survey

et al. 2020

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“…An adaptive IoT trust measurement scheme was proposed in [55], which combines the communication history and stereotypical reputation. The proposed scheme works by evaluating a user's trust value towards nodes.…”

Section: Literature Reviewmentioning

confidence: 99%

RobustTrust – A Pro-Privacy Robust Distributed Trust Management Mechanism for Internet of Things

et al. 2019

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In the promising time of the Internet, connected things have the ability to communicate and share information. The Internet of Things (IoT) cannot be implemented unless the security-related concerns have been resolved. Sharing information among different devices can compromise the private information of users. Thus, a suitable mechanism is needed to exclude the risk of malicious and compromised nodes. As follows, trust has been proposed in the literature as a useful technology to maintain users' security. Prior studies have proposed diverse trust management mechanisms to achieve adequate trust. The approach of cross-domain trust management is neglected that requires enormous considerations to address the difficulties related to cross-domain communication. In this paper, a cross-domain robust distributed trust management (RobustTrust) system is proposed, which makes a device fit for assessing trust towards different devices locally. In this system, the trust is divided into three components of security that help IoT nodes to become robust against compromised and malicious devices/nodes. The novelty of the proposed mechanism can be summarized in these aspects: A highly scalable trust mechanism, multiple components of evaluation to enhance robustness against attacks, and use of recommendations along with the feedback to build knowledge. Furthermore, the proposed mechanism is event-driven that helps nodes to evaluate trust more effectively as well as enhance the system efficiency. The proposed work is compared with the available trust evaluation schemes by concentrating on various attributes, such as trustworthiness, usability, and accuracy among others. The RobustTrust is validated by the extensive simulations considering absolute trust value's performance, the accuracy of trust estimation, and several potential attacks.

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“…The Adaptive Trust Estimation Scheme (ATES) [37] is proposed for trust management of an IoT device by using both personal and non-personal trust values. When a user interacts with an IoT device, its personal trust value is calculated through the following three methods: type, the same users' interaction history with the same type of devices is extracted, which reflects some trust level [38].…”

Section: F Atesmentioning

confidence: 99%

Trust Management Techniques for the Internet of Things: A Survey

et al. 2019

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A vision of the future Internet is introduced in such a fashion that various computing devices are connected together to form a network called Internet of Things (IoT). This network will generate massive data that may be leveraged for entertainment, security, and most importantly user trust. Yet, trust is an imperative obstruction that may hinder the IoT growth and even delay the substantial squeeze of a number of applications. In this survey, an extensive analysis of trust management techniques along with their pros and cons is presented in a different context. In comparison with other surveys, the goal is to provide a systematic description of the most relevant trust management techniques to help researchers understand that how various systems fit together to bring preferred functionalities without examining different standards. Besides, the lessons learned are presented, and the views are argued regarding the primary goal trust which is likely to play in the future Internet. INDEX TERMS Internet of Things, trust management techniques, trust contributions, trust limitations.

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An adaptive IoT trust estimation scheme combining interaction history and stereotypical reputation

Cited by 22 publications

References 9 publications

Security, Privacy and Trust for Smart Mobile- Internet of Things (M-IoT): A Survey

Security, Privacy and Trust for Smart Mobile- Internet of Things (M-IoT): A Survey

RobustTrust – A Pro-Privacy Robust Distributed Trust Management Mechanism for Internet of Things

Trust Management Techniques for the Internet of Things: A Survey

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