Biblio

Multiple Security Domains Nondeducibility, MSDND, yields results even when the attack hides important information from electronic monitors and human operators. Because MSDND is based upon modal frames, it is able to analyze the event system as it progresses rather than relying on traces of the system. Not only does it provide results as the system evolves, MSDND can point out attacks designed to be missed in other security models. This work examines information flow disruption attacks such as Stuxnet and formally explains the role that implicit trust in the cyber security of a cyber physical system (CPS) plays in the success of the attack. The fact that the attack hides behind MSDND can be used to help secure the system by modifications to break MSDND and leave the attack nowhere to hide. Modal operators are defined to allow the manipulation of belief and trust states within the model. We show how the attack hides and uses the operator's trust to remain undetected. In fact, trust in the CPS is key to the success of the attack.

The notion of trust is considered to be the cornerstone on patient-psychiatrist relationship. Thus, a trustfully background is fundamental requirement for provision of effective Ubiquitous Healthcare (UH) service. In this paper, the issue of Trust Evaluation of UH Providers when register UH environment is addressed. For that purpose a novel trust evaluation method is proposed, based on cloud theory, exploiting User Profile attributes. This theory mimics human thinking, regarding trust evaluation and captures fuzziness and randomness of this uncertain reasoning. Two case studies are investigated through simulation in MATLAB software, in order to verify the effectiveness of this novel method.

In military operation or emergency response situations, very frequently a commander will need to assemble and dynamically manage Community of Interest (COI) mobile groups to achieve a critical mission assigned despite failure, disconnection or compromise of COI members. We combine the designs of COI hierarchical management for scalability and reconfigurability with COI dynamic trust management for survivability and intrusion tolerance to compose a scalable, reconfigurable, and survivable COI management protocol for managing COI mission-oriented mobile groups in heterogeneous mobile environments. A COI mobile group in this environment would consist of heterogeneous mobile entities such as communication-device-carried personnel/robots and aerial or ground vehicles operated by humans exhibiting not only quality of service (QoS) characters, e.g., competence and cooperativeness, but also social behaviors, e.g., connectivity, intimacy and honesty. A COI commander or a subtask leader must measure trust with both social and QoS cognition depending on mission task characteristics and/or trustee properties to ensure successful mission execution. In this paper, we present a dynamic hierarchical trust management protocol that can learn from past experiences and adapt to changing environment conditions, e.g., increasing misbehaving node population, evolving hostility and node density, etc. to enhance agility and maximize application performance. With trust-based misbehaving node detection as an application, we demonstrate how our proposed COI trust management protocol is resilient to node failure, disconnection and capture events, and can help maximize application performance in terms of minimizing false negatives and positives in the presence of mobile nodes exhibiting vastly distinct QoS and social behaviors.

This study describes and evaluates a novel trust model for a range of collaborative applications. The model assumes that humans routinely choose to trust their peers by relying on few recurrent presumptions, which are domain independent and which form a recognisable trust expertise. We refer to these presumptions as trust schemes, a specialised version of Walton's argumentation schemes. Evidence is provided about the efficacy of trust schemes using a detailed experiment on an online community of 80,000 members. Results show how proposed trust schemes are more effective in trust computation when they are combined together and when their plausibility in the selected context is considered.

Mobile social networks (MSNs) facilitate connections between mobile users and allow them to find other potential users who have similar interests through mobile devices, communicate with them, and benefit from their information. As MSNs are distributed public virtual social spaces, the available information may not be trustworthy to all. Therefore, mobile users are often at risk since they may not have any prior knowledge about others who are socially connected. To address this problem, trust inference plays a critical role for establishing social links between mobile users in MSNs. Taking into account the nonsemantical representation of trust between users of the existing trust models in social networks, this paper proposes a new fuzzy inference mechanism, namely MobiFuzzyTrust, for inferring trust semantically from one mobile user to another that may not be directly connected in the trust graph of MSNs. First, a mobile context including an intersection of prestige of users, location, time, and social context is constructed. Second, a mobile context aware trust model is devised to evaluate the trust value between two mobile users efficiently. Finally, the fuzzy linguistic technique is used to express the trust between two mobile users and enhance the human's understanding of trust. Real-world mobile dataset is adopted to evaluate the performance of the MobiFuzzyTrust inference mechanism. The experimental results demonstrate that MobiFuzzyTrust can efficiently infer trust with a high precision.

Our vision in this paper is that agency, as the individual ability to intervene and tailor the system, is a crucial element in building trust in IoT technologies. Following up on this vision, we will first address the issue of agency, namely the individual capability to adopt free decisions, as a relevant driver in building trusted human-IoT relations, and how agency should be embedded in digital systems. Then we present the main challenges posed by existing approaches to implement this vision. We show then our proposal for a model-based approach that realizes the agency concept, including a prototype implementation.

Trusting a computer for a security-sensitive task (such as checking email or banking online) requires the user to know something about the computer's state. We examine research on securely capturing a computer's state, and consider the utility of this information both for improving security on the local computer (e.g., to convince the user that her computer is not infected with malware) and for communicating a remote computer's state (e.g., to enable the user to check that a web server will adequately protect her data). Although the recent "Trusted Computing" initiative has drawn both positive and negative attention to this area, we consider the older and broader topic of bootstrapping trust in a computer. We cover issues ranging from the wide collection of secure hardware that can serve as a foundation for trust, to the usability issues that arise when trying to convey computer state information to humans. This approach unifies disparate research efforts and highlights opportunities for additional work that can guide real-world improvements in computer security.

Trust is a necessary component in cybersecurity. It is a common task for a system to make a decision about whether or not to trust the credential of an entity from another domain, issued by a third party. Generally, in the cyberspace, connected and interacting systems largely rely on each other with respect to security, privacy, and performance. In their interactions, one entity or system needs to trust others, and this "trust" frequently becomes a vulnerability of that system. Aiming at mitigating the vulnerability, we are developing a computational theory of trust, as a part of our efforts towards Science of Security. Previously, we developed a formal-semantics-based calculus of trust [3, 2], in which trust can be calculated based on a trustor's direct observation on the performance of the trustee, or based on a trust network. In this paper, we construct a framework for making trust reasoning based on the observed evidence. We take privacy in cloud computing as a driving application case [5].