Many collaboration platforms are realized as service-oriented systems enabling flexible compositions of services and support of interactions. Interactions between entities in such systems do not only span software services, but also human actors. A mixed service-oriented system is therefore composed of human and software services. In open environments, interactions between people and services are highly dynamic and often influenced by the role and reputation of collaboration partners. In this paper we present an architecture for the management of trust in such mixed systems environments. In contrast to traditional solutions that typically focus on the matching of actors’ skills and competencies with collaboration requirements only, we propose a trust-based ’feedback loop’ enabling the inference and consideration of trust relationships based on observed interactions. This cycle, spanning interaction monitoring, trust analysis, trust-enabled collaboration planning, and trust-supported execution of activities and tasks, permits dynamic and trust-aware collaborations in service-oriented environments.

We argue that the traditional notion of trust as a relation among entities, while useful, becomes insufficient for emerging data-centric mobile ad hoc networks. In these systems, setting the data trust level equal to the trust level of the data- providing entity would ignore system salient features, rendering applications ineffective and systems inflexible. This would be even more so if their operation is ephemeral, i.e., characterized by short-lived associations in volatile environments. In this paper, we address this challenge by extending the traditional notion of trust to data-centric trust: trustworthiness attributed to node-reported data per se. We propose a framework for data-centric trust establishment: First, trust in each individual piece of data is computed; then multiple, related but possibly contradictory, data are combined; finally, their validity is inferred by a decision component based on one of several evidence evaluation techniques. We consider and evaluate an instantiation of our framework in vehicular networks as a case study. Our simulation results show that our scheme is highly resilient to attackers and converges stably to the correct decision.

Abstract not found

In activity-centric environments where people from different companies and disciplines work remotely together and where new virtual teams are formed and dissolved continuously, how to find the most suitable collaboration partner for a given task and how well one partner is able to collaborate with another one are challenging research questions. Determining and considering people’s professional competencies, collaboration behavior and relationships is a prerequisite to enhance the overall collaboration performance and success, because these factors highly impact on the notion of trust used to select and grade partners. In this paper we analyze these factors and their impact on trust relationships in modern service-oriented collaboration environments. We present VieTE, a framework for trust emergence therein supporting the analysis of trust between partners in various contexts and from different views. In contrast to other approaches, which mostly rely on manual and subjective user feedback, VieTE monitors automatically collaboration efforts and deduces trust between any two partners based on past collaboration, previous successes, and individual competencies. 1

This chapter introduces trust modeling and trust management as a means of managing trust in digital systems. Transforming from a social concept of trust to a digital concept, trust modeling and management help in designing and implementing a trustworthy digital system, especially in emerging distributed systems. Furthermore, the authors hope that understanding the current challenges, solutions and their limitations of trust modeling and management will not only inform researchers of a better design for establishing a trustworthy system, but also assist in the understanding of the intricate concept of trust in a digital environment.

Abstract — This paper analyzes a trust model for mobile ad hoc networks. We provide nodes with a mechanism to build a trust relationship with its neighbors. The proposed model considers the recommendation of trustworthy neighbors and the experience of the node itself. The interactions are limited to direct neighbors in order to scale on mobile networks. The results show the efficiency and the trade-off of our model in the presence of mobility. We also analyze the advantages of considering the relationship maturity, i.e. for how long nodes know each other, to evaluate the trust level. The maturity parameter can decrease the trust level error up to 50%. I.

Abstract — Slander attacks represent a significant danger to distributed reputation systems. Malicious nodes may collude to lie about the reputation of a particular neighbor and cause serious damage to the overall trust evaluation system. This paper presents and analyzes a trust model robust to slander attacks in ad hoc networks. We provide nodes with a mechanism to build a trust relationship with its neighbors. The proposed model considers the recommendation of trustworthy neighbors and the previous experiences of the node itself. The interactions are limited to direct neighbors in order to scale on mobile networks. The results show the impact of slander attacks to our trust model. We analyze how the main parameters affect the trust evaluation process under a lying collusion attack. We show that our trust model tolerate almost 40 % of liars. I.

Providing a trustworthy mobile computing platform is crucial for mobile communications, services and applications. In this dissertation, we study methodologies and mechanisms that can be used to provide a trustworthy mobile computing platform. We also present an autonomic trust management solution for a component software middleware platform targeting at an embedded device, such as a mobile phone. In the first part of the dissertation, we firstly overview the literature background of trust modeling and trust management. We propose research methodologies on the basis of a conceptual architecture of a trusted mobile environment. Further, we present a methodology to bridge disjoint trusted domains in mobile computing and communications into a trustworthy system. The second part of the dissertation contains a mechanism to sustain trust among computing platforms. The mechanism builds up a trust relationship based on the Root Trust (RT) module at a trustee platform and ensures trust sustainability according to pre-defined conditions. These conditions are approved at the time of trust establishment and enforced through the use of the pre-attested RT module until the intended purpose is fulfilled. Through applying this mechanism, we introduce a Trusted Collaboration Infrastructure (TCI) for peer-to-peer devices in order to establish trust collaboration among distributed peers. In addition, this mechanism contributes to a mobile Virtual Private Network

Abstract — Ad-hoc sensor networks are becoming more common, yet security of these networks is still an issue. Node misbehavior due to malicious attacks can impair the overall functioning of the system. Existing approaches mainly rely on cryptography to ensure data authentication and integrity. These approaches only address part of the problem of security in sensor networks. However, cryptography is not sufficient to prevent the attacks in which some of the nodes are overtaken and compromised by a malicious user. Recently, the use of reputation systems has shown positive results as a selfpolicing mechanism in ad-hoc networks. This scheme can aid in decreasing vulnerabilities which are not solved by cryptography. We look at how a distributed reputation scheme can benefit the object tracking application in sensor networks. Tracking multiple objects is one of the most important applications of the sensor network. In our setup, nodes detect misbehavior locally from observations, and assign a reputation to each of their neighbors. These reputations are used to weight node readings appropriately when performing object tracking. Over time, data from malicious nodes will not be included in the track formation process. We evaluate the reputation system experimentally and demonstrate how it improves object tracking in the presence of malicious nodes. I.

Abstract — We present a new distributed approach that establishes reputation-based trust among sensor nodes in order to identify malfunctioning and malicious sensor nodes and minimize their impact on applications. Our method adapts well to the special characteristics of wireless sensor networks, the most important being their resource limitations. Our methodology computes statistical trust and a confidence interval around the trust based on direct and indirect experiences of sensor node behavior. By considering the trust confidence interval, we are able to study the tradeoff between the tightness of the trust confidence interval with the resources used in collecting experiences. Furthermore, our approach allows dynamic scaling of redundancy levels based on the trust relationship between the nodes of a wireless sensor network. Using extensive simulations we demonstrate the benefits of our approach over an approach that uses static redundancy levels in terms of reduced energy consumption and longer life of the network. We also find that high confidence trust can be computed on each node with a relatively small memory overhead and used to determine the level of redundancy operations among nodes in the system. I.