Context-dependent Trust Decisions with Subjective Logic

A decision procedure implemented over a computational trust mechanism aims to allow for decisions to be made regarding whether some entity or information should be trusted. As recognised in the literature, trust is contextual, and we describe how such a context often translates into a confidence level which should be used to modify an underlying trust value. J{\o}sang's Subjective Logic has long been used in the trust domain, and we show that its operators are insufficient to address this problem. We therefore provide a decision-making approach about trust which also considers the notion of confidence (based on context) through the introduction of a new operator. In particular, we introduce general requirements that must be respected when combining trustworthiness and confidence degree, and demonstrate the soundness of our new operator with respect to these properties.Comment: 19 pages, 4 figures, technical report of the University of Aberdeen (preprint version

Privacy, security, and trust issues in smart environments

Recent advances in networking, handheld computing and sensor technologies have driven forward research towards the realisation of Mark Weiser's dream of calm and ubiquitous computing (variously called pervasive computing, ambient computing, active spaces, the disappearing computer or context-aware computing). In turn, this has led to the emergence of smart environments as one significant facet of research in this domain. A smart environment, or space, is a region of the real world that is extensively equipped with sensors, actuators and computing components [1]. In effect the smart space becomes a part of a larger information system: with all actions within the space potentially affecting the underlying computer applications, which may themselves affect the space through the actuators. Such smart environments have tremendous potential within many application areas to improve the utility of a space. Consider the potential offered by a smart environment that prolongs the time an elderly or infirm person can live an independent life or the potential offered by a smart environment that supports vicarious learning

Trust your instincts:The relationship between intuitive decision making and happiness

Epstein (1994; 2003) proposed that there are two cognitive information processing systems that operate in parallel: the intuitive thinking style and the rational thinking style. Decisional fit occurs when the preferred thinking style is applied to making a decision and research has shown that this fit increases the value of the outcome of a decision. Additionally, decisional fit leads to less regret, even when post hoc evaluations show the decision to be incorrect. It has not yet been determined whether decisional fit correlates with greater happiness and hence, the purpose of the current study was to investigate the difference between styles of thinking, styles of decision making and the impact of decisional fit on happiness scores. Individual differences in thinking and decision style were measured using an online interactive questionnaire (N = 100), and an ANOVA, hierarchical multiple regression, and a series of t-tests, were used to investigate the relationship between thinking style, decision style, decisional fit, and happiness, thereby addressing a gap in the existing literature. The major findings from the current study show that intuitive thinking has a strong positive correlation with happiness; that intuitive thinkers are more likely to utilize intuitive decisional style, than rational thinkers; and that when both rational and intuitive thinkers experienced decisional fit, higher ratings of happiness were reported. Explanations and recommendations for future studies are outlined in the discussion

A formal model of trust lifecycle management

The rapid development of collaborative environments over the internet has highlighted new concerns over security and trust in such global computing systems. The global computing infrastructure poses an issue of uncertainty about the potential collaborators. Reaching a trusting decision in such environments encompasses both risk and trust assessments. While much work has been done in terms of modelling trust, the investigation of the management of trust lifecycle issues with consideration of both trust and risk is less examined. Our previous work addressed the dynamic aspects of trust lifecycle with a consideration of trust formation, exploitation, and evolution. In this paper we provide an approach for formalizing these aspects. As part of the formalization of the trust lifecycle,we introduce a notion of attraction to model the effect of new pieces of evidence on our opinion. The formalization described in this paper constitutes the basis of ongoing work to investigate the properties of the model

Collaborative assessment of information provider's reliability and expertise using subjective logic

Q&A social media have gained a lot of attention during the recent years. People rely on these sites to obtain information due to a number of advantages they offer as compared to conventional sources of knowledge (e.g., asynchronous and convenient access). However, for the same question one may find highly contradicting answers, causing an ambiguity with respect to the correct information. This can be attributed to the presence of unreliable and/or non-expert users. These two attributes (reliability and expertise) significantly affect the quality of the answer/information provided. We present a novel approach for estimating these user's characteristics relying on human cognitive traits. In brief, we propose each user to monitor the activity of her peers (on the basis of responses to questions asked by her) and observe their compliance with predefined cognitive models. These observations lead to local assessments that can be further fused to obtain a reliability and expertise consensus for every other user in the social network (SN). For the aggregation part we use subjective logic. To the best of our knowledge this is the first study of this kind in the context of Q&A SN. Our proposed approach is highly distributed; each user can individually estimate the expertise and the reliability of her peers using her direct interactions with them and our framework. The online SN (OSN), which can be considered as a distributed database, performs continuous data aggregation for users expertise and reliability assessment in order to reach a consensus. We emulate a Q&A SN to examine various performance aspects of our algorithm (e.g., convergence time, responsiveness etc.). Our evaluations indicate that it can accurately assess the reliability and the expertise of a user with a small number of samples and can successfully react to the latter's behavior change, provided that the cognitive traits hold in practice. © 2011 ICST

Trust in Vehicle-to-Vehicle Communication

In traditional Pedestrian Automatic Emergency Braking (PAEB) system, vehicles equipped with onboard sensors such as radar, camera, and infrared detect pedestrians, alert the driver and/ or automatically take actions to prevent vehicle-pedestrian collision. In some situations, a vehicle may not be able to detect a pedestrian due to blind spots. Such a vehicle could benefit from the sensor data from neighboring vehicles in making such safety critical decisions. We propose a trust model for ensuring shared data are valid and trustworthy for use in making safety critical decisions. Simulation results of the proposed trust model show promise

Flow-based reputation with uncertainty: Evidence-Based Subjective Logic

The concept of reputation is widely used as a measure of trustworthiness based on ratings from members in a community. The adoption of reputation systems, however, relies on their ability to capture the actual trustworthiness of a target. Several reputation models for aggregating trust information have been proposed in the literature. The choice of model has an impact on the reliability of the aggregated trust information as well as on the procedure used to compute reputations. Two prominent models are flow-based reputation (e.g., EigenTrust, PageRank) and Subjective Logic based reputation. Flow-based models provide an automated method to aggregate trust information, but they are not able to express the level of uncertainty in the information. In contrast, Subjective Logic extends probabilistic models with an explicit notion of uncertainty, but the calculation of reputation depends on the structure of the trust network and often requires information to be discarded. These are severe drawbacks. In this work, we observe that the `opinion discounting' operation in Subjective Logic has a number of basic problems. We resolve these problems by providing a new discounting operator that describes the flow of evidence from one party to another. The adoption of our discounting rule results in a consistent Subjective Logic algebra that is entirely based on the handling of evidence. We show that the new algebra enables the construction of an automated reputation assessment procedure for arbitrary trust networks, where the calculation no longer depends on the structure of the network, and does not need to throw away any information. Thus, we obtain the best of both worlds: flow-based reputation and consistent handling of uncertainties

Arguing security: validating security requirements using structured argumentation

This paper proposes using both formal and structured informal arguments to show that an eventual realized system can satisfy its security requirements. These arguments, called 'satisfaction arguments', consist of two parts: a formal argument based upon claims about domain properties, and a set of informal arguments that justify the claims. Building on our earlier work on trust assumptions and security requirements, we show how using satisfaction arguments assists in clarifying how a system satisfies its security requirements, in the process identifying those properties of domains that are critical to the requirements