Trust Evaluation for Data Exchange in Vehicular Networks

In Vehicular (Ad-hoc) Network (VANET), besides Vehicle-to-Vehicle communications (V2V), vehicles in VANET also exchange data with Road-Side-Units (RSUs) and Cellular Base Stations (Vehicle-to-Infrastructure communications (V2I)). With the introduction of Intelligent Transport Systems (ITS), VANETs possess a great potential in enabling surveillance services. �e rapid development of wireless communication technologies recently results in empowering data exchange among vehicles, RSUs and Cellular Base Stations, improving various types of applications and services such as safety driving, route planning, traffi�c alert, and context-aware infotainment. However, the bene�fits offered by VANETs and ITS cannot be fully realized unless there is a mechanism to effectively defend against fake and erroneous information exchange from malicious or dysfunctional nodes to other vehicles and RSUs for their own purposes. In this regards, trust appears as one of the solutions for VANETs to establish secure connectivity and reliable services. The conceptual idea to tackle down this challenges is that only data from trusted vehicles is taken into account. Thus, the aim is to evaluate trust of a vehicle in exchanging high quality of information. This paper presents the trust concept, key characteristics, a trust evaluation model, and a prototype for trusted data exchange activities in VANETs

A Reputation and Knowledge Based Trust Service Platform for Trustworthy Social Internet of Things

The Internet of Things has attracted a plenty of research in this decade and imposed fascinating services where large numbers of heterogeneous-features entities socially collaborate together to solve complex scenarios. However, these entities need to trust each other prior to exchanging data or offering services. In this paper, we briefly present our ongoing project called Trust Service Platform, which offers trust assessment of any two entities in the Social Internet of Things to applications and services. We propose a trust model that incorporates both reputation properties as Recommendation and Reputation trust metrics; and knowledge-based property as Knowledge trust metric. For the trust service platform deployment, we propose a reputation system and a functional architecture with Trust Agent, Trust Broker and Trust Analysis and Management modules along with mechanisms and algorithms to deal with the three trust metrics. We also present a utility theory-based mechanism for trust calculation. To clarify our trust service platform, we describe the trust models and mechanisms in accordance with a trust car-sharing service. We believe this study offers the better understanding of the trust as a service in the platform and will impose many trust-related research challenges as the future work

Evaluation of Trust in the Internet Of Things: Models, Mechanisms And Applications

In the blooming era of the Internet of Things (IoT), trust has become a vital factor for provisioning reliable smart services without human intervention by reducing risk in autonomous decision making. However, the merging of physical objects, cyber components and humans in the IoT infrastructure has introduced new concerns for the evaluation of trust. Consequently, a large number of trust-related challenges have been unsolved yet due to the ambiguity of the concept of trust and the variety of divergent trust models and management mechanisms in different IoT scenarios. In this PhD thesis, my ultimate goal is to propose an efficient and practical trust evaluation mechanisms for any two entities in the IoT. To achieve this goal, the first important objective is to augment the generic trust concept and provide a conceptual model of trust in order to come up with a comprehensive understanding of trust, influencing factors and possible Trust Indicators (TI) in the context of IoT. Following the catalyst, as the second objective, a trust model called REK comprised of the triad Reputation, Experience and Knowledge TIs is proposed which covers multi-dimensional aspects of trust by incorporating heterogeneous information from direct observation, personal experiences to global opinions. The mathematical models and evaluation mechanisms for the three TIs in the REK trust model are proposed. Knowledge TI is as “direct trust” rendering a trustor’s understanding of a trustee in respective scenarios that can be obtained based on limited available information about characteristics of the trustee, environment and the trustor’s perspective using a variety of techniques. Experience and Reputation TIs are originated from social features and extracted based on previous interactions among entities in IoT. The mathematical models and calculation mechanisms for the Experience and Reputation TIs also proposed leveraging sociological behaviours of humans in the real-world; and being inspired by the Google PageRank in the web-ranking area, respectively. The REK Trust Model is also applied in variety of IoT scenarios such as Mobile Crowd-Sensing (MCS), Car Sharing service, Data Sharing and Exchange platform in Smart Cities and in Vehicular Networks; and for empowering Blockchain-based systems. The feasibility and effectiveness of the REK model and associated evaluation mechanisms are proved not only by the theoretical analysis but also by real-world applications deployed in our ongoing TII and Wise-IoT projects

Strengthening the Blockchain-based Internet of Value with Trust

In recent years, Blockchain has been expected to create a secure mechanism for exchanging not only for cryptocurrency but also for other types of assets without the need for a powerful and trusted third-party. This could enable a new era of the Internet usage called the Internet of Value (IoV) in which any types of assets such as intellectual and digital properties, equity and wealth can be digitized and transferred in an automated, secure, and convenient manner. In the IoV, Blockchain is used to guarantee the immutability of transactions meaning that it is impractical to retract once a transaction is confirmed. Therefore, to strengthen the IoV, before making any transactions it is crucial to evaluate trust between participants for reducing the risk of dealing with malicious peers. In this article, we clarify the concept of IoV and propose a trust-based IoV model including a system architecture, components and features. Then, we present a trust platform in the IoV considering two concepts, Experience and Reputation, originated from Social Networks for evaluating trust between two any peers in the IoV. The Experience and Reputation are characterized and calculated using mathematical models with analysis and simulation in the IoV environment. We believe this paper consolidates the understandings about IoV technologies and demonstrates how trust is evaluated and used to strengthen the IoV. It also opens important research directions on both IoV and trust in the future

From Personal Experience to Global Reputation for Trust Evaluation in the Social Internet of Things

Trust has been exploring in the era of Internet of Things (IoT) as an extension of the traditional triad of security, privacy and reliability for offering secure, reliable and seamless communications and services. It plays a crucial role in supporting IoT entities to reduce possible risks before making decisions. However, despite a large amount of trust-related research in IoT, a prevailing trust evaluation model has been still debatable and under development. In this article, we clarify the concept of trust in the Social Internet of Things (SIoT) ecosystems and propose a comprehensive trust model called REK that incorporates third-party opinions, experience and direct observation as the three Trust Indicators. As the convergence of the IoT and social network, the SIoT enables any types of entities (physical devices, smart agents and services) to establish their own social networks based on their owners relationships. We leverage this characteristic for inaugurating Experience and Reputation, which are originally two concepts from social networks, as the two paramount indicators for trust. The Experience and Reputation are characterized and modeled using mathematical analysis along with simulation experiments and analytical results. We believe our contributions offer better understandings of trust models and evaluation mechanisms in the SIoT environment, particularly the two Experience and Reputation models. This paper also opens important trust-related research directions in near future

Trust Evaluation Mechanism for User Recruitment in Mobile Crowd-Sensing in the Internet of Things

Mobile Crowd-Sensing (MCS) has appeared as a prospective solution for large-scale data collection, leveraging built-in sensors and social applications in mobile devices that enables a variety of Internet of Things (IoT) services. However, the human involvement in MCS results in a high possibility for unintentionally contributing corrupted and falsified data or intentionally spreading disinformation for malevolent purposes, consequently undermining IoT services. Therefore, recruiting trustworthy contributors plays a crucial role in collecting high quality data and providing better quality of services while minimizing the vulnerabilities and risks to MCS systems. In this article, a novel trust model called Experience-Reputation (E-R) is proposed for evaluating trust relationships between any two mobile device users in a MCS platform. To enable the E-R model, virtual interactions among the users are manipulated by considering an assessment of the quality of contributed data from such users. Based on these interactions, two indicators of trust called Experience and Reputation are calculated accordingly. By incorporating the Experience and Reputation trust indicators (TIs), trust relationships between the users are established, evaluated and maintained. Based on these trust relationships, a novel trust-based recruitment scheme is carried out for selecting the most trustworthy MCS users to contribute to data sensing tasks. In order to evaluate the performance and effectiveness of the proposed trust-based mechanism as well as the E-R trust model, we deploy several recruitment schemes in a MCS testbed which consists of both normal and malicious users. The results highlight the strength of the trust-based scheme as it delivers better quality for MCS services while being able to detect malicious users. We believe that the trust-based user recruitment offers an effective capability for selecting trustworthy users for various MCS systems and, importantly, the proposed mechanism is practical to deploy in the real world

GDPR-Compliant Personal Data Management: A Blockchain-based Solution

The General Data Protection Regulation (GDPR) gives control of personal data back to the owners by appointing higher requirements and obligations on service providers who manage and process personal data. As the verification of GDPR-compliance, handled by a supervisory authority, is irregularly conducted; it is challenging to be certified that a service provider has been continuously adhering to the GDPR. Furthermore, it is beyond the data owner’s capability to perceive whether a service provider complies with the GDPR and effectively protects her personal data. This motivates us to envision a design concept for developing a GDPR-compliant personal data management platform leveraging the emerging blockchain and smart con-tract technologies. The goals of the platform are to provide decentralised mechanisms to both service providers and data owners for processing personal data; meanwhile, empower data provenance and transparency by leveraging advanced features of the blockchain technology. The platform enables data owners to impose data usage consent, ensures only designated parties can process personal data, and logs all data activities in an immutable distributed ledger using smart contract and cryptography techniques. By honestly participating in the platform, a service provider can be endorsed by the blockchain network that it is fully GDPR-compliant; otherwise, any violation is immutably recorded and is easily figured out by associated parties. We then demonstrate the feasibility and efficiency of the proposed design concept by developing a profile management platform implemented on top of the Hyperledger Fabric permissioned blockchain framework, following by valuable analysis and discussion

High rate nitrogen removal by ANAMMOX internal circulation reactor (IC) for old landfill leachate treatment

© 2017 Elsevier Ltd This study aimed to evaluate the performance of a high rate nitrogen removal lab-scale ANAMMOX reactor, namely Internal Circulation (IC) reactor, for old landfill leachate treatment. The reactor was operated with pre-treated leachate from a pilot Partial Nitritation Reactor (PNR) using a high nitrogen loading rate ranging from 2 to 10 kg N m−3 d−1. High rate removal of nitrogen (9.52 ± 1.11 kg N m−3 d−1) was observed at an influent nitrogen concentration of 1500 mg N L−1. The specific ANAMMOX activity was found to be 0.598 ± 0.026 gN2-N gVSS−1 d−1. Analysis of ANAMMOX granules suggested that 0.5–1.0 mm size granular sludge was the dominant group. The results of DNA analysis revealed that Candidatus Kueneniastuttgartiensis was the dominant species (37.45%) in the IC reactor, whereas other species like uncultured Bacteroidetes bacterium only constituted 5.37% in the system, but they were still responsible for removing recalcitrant organic matter

Quality of Information as an indicator of Trust in the Internet of Things

The past decade has seen a rise in complexity and scale of software systems, particularly with the emerging of the Internet of Thing consisting of large scale and heterogeneous entities which results in difficulties in providing trustworthy services. To overcome such challenges, providing high quality information for IoT service provider as well as monitoring trust relationship of end-users toward the services are paramount. Such trust relationships are user-oriented and subjective phenomenon that hook on specific quality of data. Following this catalyst, we propose a mechanism to evaluate quality of information (QoI) for streaming data from sensor device; then use the QoI evaluation score as an indicator of trust. Concepts and assessment methodology for QoI along with a trust monitoring system are described. We also develop a framework that classifies streaming of data based on semantic context and generate QoI score as a relevant input for a trust monitoring component. This framework enables a dynamic trust management in the context of IoT for both end-users and services that empowers service providers to deliver trustworthy and high quality IoT services. Challenges encountered during implementation and contribution in standardization are discussed. We believe this paper offers better understanding on QoI and its importance in trust evaluation in IoT applications; also provides detailed implementation of the QoI and Trust components for real-world applications and services

Semantic Smart Contracts for Blockchain-based Services in the Internet of Things

The emerging Blockchain (BC) and Distributed Ledger technologies have come to impact a variety of domains, from capital market sectors to digital asset management in the Internet of Things (IoT). As a result, more and more BC-based decentralized applications for numerous cross-domain services have been developed. These applications implement specialized decentralized computer programs called Smart Contracts (SCs) which are deployed into BC frameworks. Although these SCs are open to public, it is challenging to discover and utilize such SCs for a wide range of usages from both systems and end-users because such SCs are already compiled in form of byte-codes without any associated meta-data. This motivates us to propose a solution called Semantic SC (SSC) which integrates RESTful semantic web technologies in SCs, deployed on the Ethereum Blockchain platform, for indexing, browsing and annotating such SCs. The solution also exposes the relevant distributed ledgers as Linked Data for enhancing the discovery capability. To achieve this goal, the OWL-S service ontology is extended by incorporating some domain specific terminologies, which are used in the development of the proposed SSCs. As a result, SSC can be utilized to enrich queries for a domain-specific terms across multiple distributed ledgers, which greatly increases the discovery capability of decentralized IoT applications and services. Contribution in standardization is also discussed. We believe that our research work takes the first steps towards connecting BC-based decentralized services with semantic web services in order to provide better IoT ecosystems