MobileTrust: Secure Knowledge Integration in VANETs

Vehicular Ad hoc NETworks (VANET) are becoming popular due to the emergence of the Internet of Things and ambient intelligence applications. In such networks, secure resource sharing functionality is accomplished by incorporating trust schemes. Current solutions adopt peer-to-peer technologies that can cover the large operational area. However, these systems fail to capture some inherent properties of VANETs, such as fast and ephemeral interaction, making robust trust evaluation of crowdsourcing challenging. In this article, we propose MobileTrust—a hybrid trust-based system for secure resource sharing in VANETs. The proposal is a breakthrough in centralized trust computing that utilizes cloud and upcoming 5G technologies to provide robust trust establishment with global scalability. The ad hoc communication is energy-efficient and protects the system against threats that are not countered by the current settings. To evaluate its performance and effectiveness, MobileTrust is modelled in the SUMO simulator and tested on the traffic features of the small-size German city of Eichstatt. Similar schemes are implemented in the same platform to provide a fair comparison. Moreover, MobileTrust is deployed on a typical embedded system platform and applied on a real smart car installation for monitoring traffic and road-state parameters of an urban application. The proposed system is developed under the EU-founded THREAT-ARREST project, to provide security, privacy, and trust in an intelligent and energy-aware transportation scenario, bringing closer the vision of sustainable circular economy

A Survey on Trust Computation in the Internet of Things

Internet of Things defines a large number of diverse entities and services which interconnect with each other and individually or cooperatively operate depending on context, conditions and environments, produce a huge personal and sensitive data. In this scenario, the satisfaction of privacy, security and trust plays a critical role in the success of the Internet of Things. Trust here can be considered as a key property to establish trustworthy and seamless connectivity among entities and to guarantee secure services and applications. The aim of this study is to provide a survey on various trust computation strategies and identify future trends in the field. We discuss trust computation methods under several aspects and provide comparison of the approaches based on trust features, performance, advantages, weaknesses and limitations of each strategy. Finally the research discuss on the gap of the trust literature and raise some research directions in trust computation in the Internet of Things

MobileTrust: Secure Knowledge Integration in VANETs

Vehicular Ad hoc NETworks (VANET) are becoming popular due to the emergence of the Internet of Things and ambient intelligence applications. In such networks, secure resource sharing functionality is accomplished by incorporating trust schemes. Current solutions adopt peer-to-peer technologies that can cover the large operational area. However, these systems fail to capture some inherent properties of VANETs, such as fast and ephemeral interaction, making robust trust evaluation of crowdsourcing challenging. In this article, we propose MobileTrust – a hybrid trust-based system for secure resource sharing in VANETs. The proposal is a breakthrough in centralized trust computing that utilizes cloud and upcoming 5G technologies in order to provide robust trust establishment with global scalability. The ad hoc communication is energy-efficient and protects the system against threats that are not countered by the current settings. To evaluate its performance and effectiveness, MobileTrust is modelled in the SUMO simulator and tested on the traffic features of the small-size German city of Eichstatt. Similar schemes are implemented in the same platform in order to provide a fair comparison. Moreover, MobileTrust is deployed on a typical embedded system platform and applied on a real smart car installation for monitoring traffic and road-state parameters of an urban application. The proposed system is developed under the EU-founded THREAT-ARREST project, to provide security, privacy, and trust in an intelligent and energy-aware transportation scenario, bringing closer the vision of sustainable circular economy

Trust Evaluation in the IoT Environment

Along with the many benefits of IoT, its heterogeneity brings a new challenge to establish a trustworthy environment among the objects due to the absence of proper enforcement mechanisms. Further, it can be observed that often these encounters are addressed only concerning the security and privacy matters involved. However, such common network security measures are not adequate to preserve the integrity of information and services exchanged over the internet. Hence, they remain vulnerable to threats ranging from the risks of data management at the cyber-physical layers, to the potential discrimination at the social layer. Therefore, trust in IoT can be considered as a key property to enforce trust among objects to guarantee trustworthy services. Typically, trust revolves around assurance and confidence that people, data, entities, information, or processes will function or behave in expected ways. However, trust enforcement in an artificial society like IoT is far more difficult, as the things do not have an inherited judgmental ability to assess risks and other influencing factors to evaluate trust as humans do. Hence, it is important to quantify the perception of trust such that it can be understood by the artificial agents. In computer science, trust is considered as a computational value depicted by a relationship between trustor and trustee, described in a specific context, measured by trust metrics, and evaluated by a mechanism. Several mechanisms about trust evaluation can be found in the literature. Among them, most of the work has deviated towards security and privacy issues instead of considering the universal meaning of trust and its dynamic nature. Furthermore, they lack a proper trust evaluation model and management platform that addresses all aspects of trust establishment. Hence, it is almost impossible to bring all these solutions to one place and develop a common platform that resolves end-to-end trust issues in a digital environment. Therefore, this thesis takes an attempt to fill these spaces through the following research work. First, this work proposes concrete definitions to formally identify trust as a computational concept and its characteristics. Next, a well-defined trust evaluation model is proposed to identify, evaluate and create trust relationships among objects for calculating trust. Then a trust management platform is presented identifying the major tasks of trust enforcement process including trust data collection, trust data management, trust information analysis, dissemination of trust information and trust information lifecycle management. Next, the thesis proposes several approaches to assess trust attributes and thereby the trust metrics of the above model for trust evaluation. Further, to minimize dependencies with human interactions in evaluating trust, an adaptive trust evaluation model is presented based on the machine learning techniques. From a standardization point of view, the scope of the current standards on network security and cybersecurity needs to be expanded to take trust issues into consideration. Hence, this thesis has provided several inputs towards standardization on trust, including a computational definition of trust, a trust evaluation model targeting both object and data trust, and platform to manage the trust evaluation process

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

A Scalable Trust Management scheme for Mobile Ad Hoc Networks

Mobile ad hoc networks MANETs, have special resource requirements and different topology features, they establish themselves on fly without reliance on centralized or specialized entities such as base stations. All the nodes must cooperate with each other in order to send packets, forwarding packets, responding to routing messages, sending recommendations, among others, Cooperating nodes must trust each other. In MANETs, an untrustworthy node can wreak considerable damage and adversely affect the quality and reliability of data. Therefore, analyzing the trust level of a node has a positive influence on the confidence with which an entity conducts transactions with that node. This thesis presents a new trust management scheme to assign trust levels for spaces or nodes in ad hoc networks. The scheme emulates the human model which depends on the previous individual experience and on the intercession or recommendation of other spaces in the same radio range. The trust level considers the recommendation of trustworthy neighbors and their own experience. For the recommendation computation, we take into account not only the trust level, but also its accuracy and the relationship maturity. The relationship rationality -maturity-, allows nodes to improve the efficiency of the proposed model for mobile scenarios. We also introduce the Contribution Exchange Protocol (CEP) which allows nodes to exchange Intercessions and recommendation about their neighbors without disseminating the trust information over the entire network. Instead, nodes only need to keep and exchange trust information about nodes within the radio range. Without the need for a global trust knowledge. Different from most related works, this scheme improves scalability by restricting nodes to keep and exchange trust information solely with direct neighbors, that is, neighbors within the radio range. We have developed a simulator, which is specifically designed for this model, in order to evaluate and identify the main characteristics of the proposed system. Simulation results show the correctness of this model in a single-hop network. Extending the analysis to mobile multihop networks, shows the benefits of the maturity relationship concept, i.e. for how long nodes know each other, the maturity parameter can decrease the trust level error up to 50%. The results show the effectiveness of the system and the influence of main parameters in the presence of mobility. At last, we analyze the performance of the CEP protocol and show its scalability. We show that this implementation of CEP can significantly reduce the number messages

Hybrid routing in delay tolerant networks

This work addresses the integration of today\\u27s infrastructure-based networks with infrastructure-less networks. The resulting Hybrid Routing System allows for communication over both network types and can help to overcome cost, communication, and overload problems. Mobility aspect resulting from infrastructure-less networks are analyzed and analytical models developed. For development and deployment of the Hybrid Routing System an overlay-based framework is presented

Hybrid Routing in Delay Tolerant Networks

This work addresses the integration of today\u27s infrastructure-based networks with infrastructure-less networks. The resulting Hybrid Routing System allows for communication over both network types and can help to overcome cost, communication, and overload problems. Mobility aspect resulting from infrastructure-less networks are analyzed and analytical models developed. For development and deployment of the Hybrid Routing System an overlay-based framework is presented

A Lightweight Attribute-Based Access Control System for IoT.

The evolution of the Internet of things (IoT) has made a significant impact on our daily and professional life. Home and office automation are now even easier with the implementation of IoT. Multiple sensors are connected to monitor the production line, or to control an unmanned environment is now a reality. Sensors are now smart enough to sense an environment and also communicate over the Internet. That is why, implementing an IoT system within the production line, hospitals, office space, or at home could be beneficial as a human can interact over the Internet at any time to know the environment. 61% of International Data Corporation (IDC) surveyed organizations are actively pursuing IoT initiatives, and 6.8% of the average IT budgets is also being allocated to IoT initiatives. However, the security risks are still unknown, and 34% of respondents pointed out that data safety is their primary concern [1]. IoT sensors are being open to the users with portable/mobile devices. These mobile devices have enough computational power and make it di cult to track down who is using the data or resources. That is why this research focuses on proposing a dynamic access control system for portable devices in IoT environment. The proposed architecture evaluates user context information from mobile devices and calculates trust value by matching with de ned policies to mitigate IoT risks. The cloud application acts as a trust module or gatekeeper that provides the authorization access to READ, WRITE, and control the IoT sensor. The goal of this thesis is to offer an access control system that is dynamic, flexible, and lightweight. This proposed access control architecture can secure IoT sensors as well as protect sensor data. A prototype of the working model of the cloud, mobile application, and sensors is developed to prove the concept and evaluated against automated generated web requests to measure the response time and performance overhead. The results show that the proposed system requires less interaction time than the state-of-the-art methods