As people go about their lives, they form a variety of social relationships, such as family, friends, colleagues, and acquaintances, and these relationships differ in their strength, indicating the level of trust among these people. The trend in these relationships is for people to trust those who they have met in real life more than unfamiliar people whom they have only met online. In online social network sites the objective is to make it possible for users to post information and share albums, diaries, videos, and experiences with a list of contacts who are real-world friends and/or like-minded online friends. However, with the growth of online social services, the need for identifying trustworthy people has become a primary focus in order to protect users’ vast amounts of information from being misused by unreliable users. In this thesis, we introduce the Capacity- first algorithm for identifying a local group of trusted people within a network. In order to achieve the outlined goals, the algorithm adapts the Advogato trust metric by incorporating weighted social relationships. The Capacity-first algorithm determines all possible reliable users within the network of a targeted user and prevents malicious users from accessing their personal network. In order to evaluate our algorithm, we conduct experiments to measure its performance against other well-known baseline algorithms. The experimental results show that our algorithm’s performance is better than existing alternatives in finding all possible trustworthy users and blocking unreliable ones from violating users’ privacy.

As people go about their lives, they form a variety of social relationships, such as family, friends, colleagues, and acquaintances, and these relationships differ in their strength, indicating the level of trust among these people. The trend in these relationships is for people to trust those who they have met in real life more than unfamiliar people whom they have only met online. In online social network sites the objective is to make it possible for users to post information and share albums, diaries, videos, and experiences with a list of contacts who are real-world friends and/or like-minded online friends. However, with the growth of online social services, the need for identifying trustworthy people has become a primary focus in order to protect users’ vast amounts of information from being misused by unreliable users. In this thesis, we introduce the Capacity- first algorithm for identifying a local group of trusted people within a network. In order to achieve the outlined goals, the algorithm adapts the Advogato trust metric by incorporating weighted social relationships. The Capacity-first algorithm determines all possible reliable users within the network of a targeted user and prevents malicious users from accessing their personal network. In order to evaluate our algorithm, we conduct experiments to measure its performance against other well-known baseline algorithms. The experimental results show that our algorithm’s performance is better than existing alternatives in finding all possible trustworthy users and blocking unreliable ones from violating users’ privacy.

As people go about their lives, they form a variety of social relationships, such as family, friends, colleagues, and acquaintances, and these relationships differ in their strength, indicating the level of trust among these people. The trend in these relationships is for people to trust those who they have met in real life more than unfamiliar people whom they have only met online. In online social network sites the objective is to make it possible for users to post information and share albums, diaries, videos, and experiences with a list of contacts who are real-world friends and/or like-minded online friends. However, with the growth of online social services, the need for identifying trustworthy people has become a primary focus in order to protect users’ vast amounts of information from being misused by unreliable users. In this thesis, we introduce the Capacity- first algorithm for identifying a local group of trusted people within a network. In order to achieve the outlined goals, the algorithm adapts the Advogato trust metric by incorporating weighted social relationships. The Capacity-first algorithm determines all possible reliable users within the network of a targeted user and prevents malicious users from accessing their personal network. In order to evaluate our algorithm, we conduct experiments to measure its performance against other well-known baseline algorithms. The experimental results show that our algorithm’s performance is better than existing alternatives in finding all possible trustworthy users and blocking unreliable ones from violating users’ privacy.

Distributed systems like e-commerce and e-market places, peer-to-peer networks, social networks, and mobile ad hoc networks require cooperation among the participating entities to guarantee the formation and sustained existence of network services. The reliability of interactions among anonymous entities is a significant issue in such environments. The distributed entities establish connections to interact with others, which may include selfish and misbehaving entities and result in bad experiences. Therefore, trustworthiness evaluation using trust management techniques has become a significant issue in securing these environments to allow entities decide on the reliability and trustworthiness of other entities, besides it helps coping with defection problems and stimulating entities to cooperate. Recent models on evaluating trustworthiness in distributed systems have heavily focused on assessing trustworthiness of entities and isolate misbehaviours based on single trust metrics. Less effort has been put on the investigation of the subjective nature and differences in the way trustworthiness is perceived to produce a composite multidimensional trust metrics to overcome the limitation of considering single trust metric. In the light of this context, this thesis concerns the evaluation of entities’ trustworthiness by the design and investigation of trust metrics that are computed using multiple properties of trust and considering environment. Based on the concept of probabilistic theory of trust management technique, this thesis models trust systems and designs cooperation techniques to evaluate trustworthiness in mobile ad hoc networks (MANETs). A recommendation based trust model with multi-parameters filtering algorithm, and multidimensional metric based on social and QoS trust model are proposed to secure MANETs. Effectiveness of each of these models in evaluating trustworthiness and discovering misbehaving nodes prior to interactions, as well as their influence on the network performance has been investigated. The results of investigating both the trustworthiness evaluation and the network performance are promising.

Distributed systems like e-commerce and e-market places, peer-to-peer networks, social networks, and mobile ad hoc networks require cooperation among the participating entities to guarantee the formation and sustained existence of network services. The reliability of interactions among anonymous entities is a significant issue in such environments. The distributed entities establish connections to interact with others, which may include selfish and misbehaving entities and result in bad experiences. Therefore, trustworthiness evaluation using trust management techniques has become a significant issue in securing these environments to allow entities decide on the reliability and trustworthiness of other entities, besides it helps coping with defection problems and stimulating entities to cooperate. Recent models on evaluating trustworthiness in distributed systems have heavily focused on assessing trustworthiness of entities and isolate misbehaviours based on single trust metrics. Less effort has been put on the investigation of the subjective nature and differences in the way trustworthiness is perceived to produce a composite multidimensional trust metrics to overcome the limitation of considering single trust metric. In the light of this context, this thesis concerns the evaluation of entities’ trustworthiness by the design and investigation of trust metrics that are computed using multiple properties of trust and considering environment. Based on the concept of probabilistic theory of trust management technique, this thesis models trust systems and designs cooperation techniques to evaluate trustworthiness in mobile ad hoc networks (MANETs). A recommendation based trust model with multi-parameters filtering algorithm, and multidimensional metric based on social and QoS trust model are proposed to secure MANETs. Effectiveness of each of these models in evaluating trustworthiness and discovering misbehaving nodes prior to interactions, as well as their influence on the network performance has been investigated. The results of investigating both the trustworthiness evaluation and the network performance are promising. / Ministry of Higher Education in Libya and the Libyan Cultural Attaché bureau in London

Trust is a core construct of our social lives, influencing how we interact with other individuals that are part of our social circle. Whether at work, in teams, or with friends and family, trust influences how much information we exchange with the other individuals and how we interact as a dyad. Defined as risk acceptance behaviour in situations where there is dependency between the parties, trusting another person means accepting some risks to benefit from the social integration of tasks and knowledge. In an institutional environment, trust is a core component of teamwork dynamics, having a strong influence on team effectiveness and performance. Teams are the backbone of current industry, research, healthcare, and business domains. Teams have the power to increase the momentum of projects and tasks, and may also benefit from the collective body of knowledge brought by experts from different fields. Teamwork also brings new constraints to the interpersonal dynamic; for instance, a lack of interpersonal trust can deeply impact the performance and effectiveness of a team. Without trust, communication and interaction between team members can be significantly impaired, limiting the ability of a team to perform and to become effective. As teams move to non-collocated work, the development of trust is restricted by the limited media richness of communication channels. The perceptual mechanisms that compose the major part of the trust development process become constrained, as behavioural cues are not readily available through Computer Mediated Communication Systems (CMCSs). For this reason, virtual teams can suffer from low, fragile, and delayed trust, impairing team effectiveness and performance. Given the increasing prevalence of non-collocated teams, there is a need for the development of a toolset for understanding, measuring, and fostering trust in distributed teamwork environments. The existing literature provides only a partial understanding of the trust formation process and does not encompass a detailed description of the perceptual mechanisms that would help explain trust formation and allow the design of interventions tailored at targeting trust. I started by developing a model that explains trust formation and the perceptual mechanisms involved in this process, in which I also incorporate the distinction between intuitive trust and calculative confidence. The Human Factors Interpersonal Trust State Formation Model developed in this thesis helps explain the situational variability of interpersonal trust, a very important characteristic to consider when using the knowledge about trust formation to inform design. This model explains how researchers and practitioners can develop designs and interventions to foster trust based on increasing the perception of trust-building cues. Similarly, good trust metrics must capture both a measurement of trust between two people and provide information about how each trust cue influences the formation of the trust state. With the intent of incorporating situational sensitivity to a trust metric, I designed the Quick Trust Assessment Scale (QTAS), based on the NASA-TLX structure, using a combination of direct rating of subjective subscales of trust, with a pairwise comparison of each pair of subscales. I evaluated the QTAS using Crombach’s Alpha and Factor Analysis. The results showed high internal validity and identified one component for extraction from the metric, since this component focused on measuring a construct outside the interest of the QTAS. The QTAS is the first trust metric to be developed that includes a component to measure the situational variability of trust. The next component of this thesis focuses on identifying and testing ways to foster trust in a specific other through electronic communication. To achieve this objective, I initially conducted an ethnographic study to identify how team members foster trust in face-to-face collaborations and which trust cues are most often exchanged. In this study, I identified the effect of a third party on fostering trust (liaison) and five behaviours, or trust building cues, that were most used: recommendation, validation, expertise, social network, and benevolence/willingness to help. These five behaviours were later converted into interface design objects (trust tokens), in the form of badges, to be used in CMCSs and social network environments, acting as surrogates for the missing trust cues. The trust tokens were tested on simulated social network interfaces to identify the effects of multiple latent factors. Results showed that the use of the trust tokens is independent of gender, age, education level, and personality type. However, use was dependent on the type of risk the participants were facing and their cultural background. Although trust tokens are effective in fostering trust behaviour, there was not a unified solution for every type of situation. In order to further validate the situational dependence of trust decisions, I have evaluated two major variables of interest. Through experimental manipulation, I demonstrated the influence of (1) situational risk and (2) cultural background on the use of trust cues. These findings are of relevance for the design of systems that support the development of interpersonal trust as they raise the awareness of the highly variable nature of trust. In order for designers, researchers, and practitioners to successfully influence trust behaviour in teamwork environments, they need to include interpersonal trust as a variable of interest in the design requirements of systems that support teamwork, as well as carefully consider the impact of their interventions, as their interventions will influence variably, depending on the situation and target population. Ultimately, this research program demonstrates the importance of including interpersonal trust as a variable of interest in and as a requirement for the design of systems that support teamwork and collaboration.