A Time-Aware Similarity-Based Trust Computational Model for Social Internet of Things

Sagar, Subhash; Mahmood, Adnan; Pabani, Jitander Kumar; Sheng, Quan Z.

doi:10.1109/globecom42002.2020.9322540

Cited by 22 publications

(12 citation statements)

References 19 publications

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“…To determine the final trust value of one node as perceived by another node in time 't' based on TAs [104].…”

Section: Scenariosmentioning

confidence: 99%

“…The studies are represented by their reference numbers. Hybrid/ Semi-Centralized [81], [82], [84], [46], [88], [95], [112], [114], [115], [119] [79], [63], [85], [86], [87], [7], [89], [90], [91], [92], [93], [94], [95], [96], [98], [99], [100], [101], [58], [102], [103], [104], [77], [105], [106], [107], [108], [109], [110], [111], [78], [113], [114] [132], [133] [71], [80], [83], [97]…”

Section: ) Trust Values Propagation Schemementioning

confidence: 99%

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Trust Management in Social Internet of Things (SIoT): A Survey

et al. 2022

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A survey on trust management in the Social Internet of Things (SIoT) is provided, beginning with a discussion of SIoT architectures and relationships. Using a variety of publication databases, we describe efforts that focus on various trust management aspects of SIoT . Trust management models comprise three themes: trust computation, aggregation, and updates. Our study presents a detailed discussion of all three steps. Trust computation and trust aggregation depend upon Trust Attributes (TAs) for the calculation of local and global trust values. Our paper discusses many strategies for aggregating trust, but "Weighted Sum" is the most frequently used in the relevant studies. Our paper addresses trust computation and aggregation scenarios. Our work classifies research by TAs (Social Trust, Quality of Service). We've categorized the research (reputation-based, recommendation-based, knowledge-based) depending on the types of feedback/opinions used to calculate trust values (global feedback/opinion, feedback from a friend, trustor's own opinion considering the trustee's information). Our work classifies studies (policy-based, prediction-based, weighted sum-based/weighted linear combination-based) by trust computation/aggregation approach. Two trust-update schemes are discussed: time-driven and event-driven schemes, while most trust management models utilize an event-driven scheme. Both trust computation and aggregation need propagating trust values in a centralized, decentralized, or semi-centralized way. Our study covers classifying research by trust updates and propagation techniques. Trust models should provide resiliency to SIoT attacks. This analysis classifies SIoT attacks as collaborative or individual. We also discuss scenarios depicted in the relevant studies to incorporate resistance against trust-related attacks in SIoT. Studies suggest context-based or context-free trust management strategies. Our study categorizes studies based on context-based or contextfree approaches. To gain the benefits of an immutable, privacy-preserving approach, a future trust management system should utilize Blockchain technology to support non-repudiation and tracking of trust relationships.

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“…To determine the final trust value of one node as perceived by another node in time 't' based on TAs [104].…”

Section: Scenariosmentioning

confidence: 99%

Section: ) Trust Values Propagation Schemementioning

confidence: 99%

Trust Management in Social Internet of Things (SIoT): A Survey

et al. 2022

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“…Sagar et al [41] designed another time-aware trust computational model that employed direct and indirect trust metrics for calculating the trust values of nodes. A weighted sum technique was used to aggregate similarity-based direct trust features; Community-of-Interest Similarity, Friendship Similarity, Co-work Similarity, and recommendations from neighboring to calculate a node's final trust score.…”

Section: Existing State-of-the-art Trust Computation Modelsmentioning

confidence: 99%

A Survey of Trust Management Schemes for Social Internet of Things

Kuseh

Nunoo‐Mensah

Klogo

et al. 2022

Inf. J. Ilm. Bid. Teknol. Inf. dan Komun.

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Social Internet of Things (SIoT) involves integrating social networking concepts in the Internet of Things (IoT) to enhance social interactions among IoT objects and users. SIoT is envisaged to provide adequate service selection and discovery. Trust is an essential factor whenever social concepts are discussed in communication networks. Trust usually leads to a mutual relationship between two parties (i.e., the trustor and trustee) where they both enjoy mutual benefits. For secure social relationships, Trust management (TM) is a crucial feature of SIoT. The primary aim of this work is to provide a comprehensive review of trust management proposals/schemes available for SIoT. Four main trust calculation algorithms for trust management were selected for this review, and they were examined in detail. The IEEE Xplore, Scopus, ResearchGate, and Google Scholar databases were searched for articles containing the terms "Trust aggregation approaches in IoT", and "Trust computation in SIoT" with a particular emphasis on works published between 2018 and 2021. The paper also discussed the pros and cons of each TM technique, trust metrics/features, contributions, and limitations of the state-of-the-art SIoT TM proposals in the literature. The paper further provides open issues and possible research directions for entry-level researchers in the domain of SIoT.

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“…Recently, there has been an increasing interest by a number of researchers to model the trustworthiness management in SIoT since it is one of the fundamental concerns in SIoT research [11][12][13] [14]. A wide range of facets can be contemplated for ascertaining the trustworthiness, including but not limited to, social relationships, reputation, quality-of-service, context (i.e., energy and time), etc.…”

Section: State-of-the-artmentioning

confidence: 99%

Towards a Machine Learning-driven Trust Evaluation Model for Social Internet of Things: A Time-aware Approach

Sagar¹,

Mahmood²,

Sheng³

et al. 2021

Preprint

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The emerging paradigm of the Social Internet of Things (SIoT) has transformed the traditional notion of the Internet of Things (IoT) into a social network of billions of interconnected smart objects by integrating social networking facets into the same. In SIoT, objects can establish social relationships in an autonomous manner and interact with the other objects in the network based on their social behaviour. A fundamental problem that needs attention is establishing of these relationships in a reliable and trusted way, i.e., establishing trustworthy relationships and building trust amongst objects. In addition, it is also indispensable to ascertain and predict an object's behaviour in the SIoT network over a period of time. Accordingly, in this paper, we have proposed an efficient time-aware machine learning-driven trust evaluation model to address this particular issue. The envisaged model deliberates social relationships in terms of friendship and community-interest, and further takes into consideration the working relationships and cooperativeness (object-object interactions) as trust parameters to quantify the trustworthiness of an object. Subsequently, in contrast to the traditional weighted sum heuristics, a machine learning-driven aggregation scheme is delineated to synthesize these trust parameters to ascertain a single trust score. The experimental results demonstrate that the proposed model can efficiently segregates the trustworthy and untrustworthy objects within a network, and further provides the insight on how the trust of an object varies with time along with depicting the effect of each trust parameter on a trust score.

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A Time-Aware Similarity-Based Trust Computational Model for Social Internet of Things

Cited by 22 publications

References 19 publications

Trust Management in Social Internet of Things (SIoT): A Survey

Trust Management in Social Internet of Things (SIoT): A Survey

A Survey of Trust Management Schemes for Social Internet of Things

Towards a Machine Learning-driven Trust Evaluation Model for Social Internet of Things: A Time-aware Approach

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