Trust–SIoT: Toward Trustworthy Object Classification in the Social Internet of Things

Abstract

The emerging yet promising paradigm of the Social Internet of Things (SIoT) integrates the notion of the Internet of Things with human social networks. In SIoT, objects, i.e., things, have the capability to socialize with the other objects in the SIoT network and can establish their social network autonomously by modeling human behaviour. The notion of trust is imperative in realizing these characteristics of socialization in order to assess the reliability of autonomous collaboration. The perception of trust is evolving in the era of SIoT as an extension to traditional security triads in an attempt to offer secure and reliable services, and is considered as an imperative aspect of any SIoT system for minimizing the probable risk of autonomous decision-making. This research investigates the idea of trust quantification by employing trust measurement in terms of direct trust, indirect trust as a recommendation, and the degree of SIoT relationships in terms of social similarities (communityof-interest, friendship, and co-work relationships). A weighted sum approach is subsequently employed to synthesize all the trust features in order to ascertain a single trust score. The experimental evaluation demonstrates the effectiveness of the proposed model in segregating trustworthy and untrustworthy objects and via identifying the dynamic behaviour (i.e., trust-related attacks) of the SIoT objects.

Toward Spectrum Efficiency and Reliability for Heterogeneous Users in CR-Enabled Social Internet of Things

“…This implies that SIoT needs more spectral resources compared to IoT for its additional intractability with other SIoT devices and users in automated interaction. Therefore, it is more important to investigate spectrum efficiency considering the huge spectrum of SIoT [5].…”

“…However, the existing networks are already in need of more spectrum, and extensive research is being conducted to develop new techniques for utilizing the existing spectrum more effi-ciently. Among these techniques, cognitive radio (CR) has attracted significant interest from the research community [5], [6].…”

Access Control Mechanism for Social Internet of Things

“…Like human social networks, SIoT enables the IoT devices to make friends [4,5] by autonomously establishing a device-to-device interaction with (apriori known as well as unknown) devices based on rules specified by the device owners, and, to discover and select more services [6] by navigating the social network of IoT devices based on a Friend of A Friend (FoAF) relationships [7]. In addition to the service discovery and network navigability, an SIoT-based system require to include (i) relationship management [8] to manage the dynamic interactions with permanently deployed or occasionally coexist devices, (ii) trustworthiness management to ensure that friendship-based devices are trusted [9,10] and as a consequence ensure the credibility, reliability and accuracy of the provided data [11], and (iii) security. As the social network of IoT devices continues to grow by discovering new services and establishing new social relationships, serious security concerns come out.…”

Towards Better Trust in Human-Machine Teaming through Explainable Dependability

“…Another orthogonal line of research focuses on conceptual frameworks for trust in autonomous systems per-se [9], and in human-machine interactions in general [4], [13], [16]. Trust definition and management encompass multiple facets elicited in recent surveys [13], [16], [25], including dependability and explainability aspects that represent our main focus. The lifecycle of trust management with a definition of properties, metrics and possible solutions in the area of social Internet of Things is illustrated in [15].…”