Modal Tableaux for Verifying Security Protocols

To develop theories to specify and reason about various aspects of multi-agent systems, many researchers have proposed the use of modal logics such as belief logics, logics of knowledge, and logics of norms. As multi-agent systems operate in dynamic environments, there is also a need to model the evolution of multi-agent systems through time. In order to introduce a temporal dimension to a belief logic, we combine it with a linear-time temporal logic using a powerful technique called fibring for combining logics. We describe a labelled modal tableaux system for a fibred belief logic (FL) which can be used to automatically verify correctness of inter-agent stream authentication protocols. With the resulting fibred belief logic and its associated modal tableaux, one is able to build theories of trust for the description of, and reasoning about, multi-agent systems operating in dynamic environments

Modal tableaux for verifying stream authentication protocols

To develop theories to specify and reason about various aspects of multi-agent systems, many researchers have proposed the use of modal logics such as belief logics, logics of knowledge, and logics of norms. As multi-agent systems operate in dynamic environments, there is also a need to model the evolution of multi-agent systems through time. In order to introduce a temporal dimension to a belief logic, we combine it with a linear-time temporal logic using a powerful technique called fibring for combining logics. We describe a labelled modal tableaux system for the resulting fibred belief logic (FL) which can be used to automatically verify correctness of inter-agent stream authentication protocols. With the resulting fibred belief logic and its associated modal tableaux, one is able to build theories of trust for the description of, and reasoning about, multi-agent systems operating in dynamic environments

A Dynamic Epistemic Logic for Abstract Argumentation

This paper introduces a multi-agent dynamic epistemic logic for abstract argumenta- tion. Its main motivation is to build a general framework for modelling the dynamics of a debate, which entails reasoning about goals, beliefs, as well as policies of com- munication and information update by the participants. After locating our proposal and introducing the relevant tools from abstract argumentation, we proceed to build a three-tiered logical approach. At the first level, we use the language of propositional logic to encode states of a multi-agent debate. This language allows to specify which arguments any agent is aware of, as well as their subjective justification status. We then extend our language and semantics to that of epistemic logic, in order to model individuals’ beliefs about the state of the debate, which includes uncertainty about the information available to others. As a third step, we introduce a framework of dynamic epistemic logic and its semantics, which is essentially based on so-called event models with factual change. We provide completeness results for a number of systems and show how existing formalisms for argumentation dynamics and unquantified uncerSynthese tainty can be reduced to their semantics. The resulting framework allows reasoning about subtle epistemic and argumentative updates—such as the effects of different levels of trust in a source—and more in general about the epistemic dimensions of strategic communication

Verification of temporal-epistemic properties of access control systems

Verification of access control systems against vulnerabilities has always been a challenging problem in the world of computer security. The complication of security policies in large- scale multi-agent systems increases the possible existence of vulnerabilities as a result of mistakes in policy definition. This thesis explores automated methods in order to verify temporal and epistemic properties of access control systems. While temporal property verification can reveal a considerable number of security holes, verification of epistemic properties in multi-agent systems enable us to infer about agents' knowledge in the system and hence, to detect unauthorized information flow. This thesis first presents a framework for knowledge-based verification of dynamic access control policies. This framework models a coalition-based system, which evaluates if a property or a goal can be achieved by a coalition of agents restricted by a set of permissions defined in the policy. Knowledge is restricted to the information that agents can acquire by reading system information in order to increase time and memory efficiency. The framework has its own model-checking method and is implemented in Java and released as an open source tool named \char{cmmi10}{0x50}\char{cmmi10}{0x6f}\char{cmmi10}{0x6c}\char{cmmi10}{0x69}\char{cmmi10}{0x56}\char{cmmi10}{0x65}\char{cmmi10}{0x72}. In order to detect information leakage as a result of reasoning, the second part of this thesis presents a complimentary technique that evaluates access control policies over temporal-epistemic properties where the knowledge is gained by reasoning. We will demonstrate several case studies for a subset of properties that deal with reasoning about knowledge. To increase the efficiency, we develop an automated abstraction refinement technique for evaluating temporal-epistemic properties. For the last part of the thesis, we develop a sound and complete algorithm in order to identify information leakage in Datalog-based trust management systems

Metamodelo para adaptação de confiança e reputação em sistemas multiagente dinâmicos

Tese (doutorado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2013.Modelos computacionais de confiança e reputação são elementos-chave no projeto de sistemas multiagente abertos. Eles oferecem um meio de avaliar e reduzir o risco de cooperação na presença de incerteza. No entanto, os modelos propostos na literatura não consideram os custos envolvidos na sua aplicação e como os modelos são afetados pela dinamicidade do ambiente. Neste trabalho, um metamodelo para adaptação de confiança a e reputação em sistemas multiagente dinâmicos é proposto. O metamodelo tem como finalidade complementar os modelos de confiança e reputação já existentes, permitindo que agentes deliberativos possam raciocinar sobre os componentes do modelo em uso e reagir a mudança as no ambiente. O processo de adaptação é realizado ajustando a configuração do modelo adotado para melhor se adequar às condições atuais. É demonstrado como o metamodelo pode ser aplicado a modelos propostos na literatura e como planos de adaptação podem ser utilizados para ajustar seus componentes dinamicamente para melhorar seu desempenho. Um mecanismo de aprendizagem, incluindo uma prova de conceito baseada em algoritmos genéticos, é proposto para identificar novos planos de adaptação para cenários similares. Por fim, a avaliação experimental da aplicação do metamodelo e do mecanismo de aprendizagem mostra melhorias significativas em comparação com o uso de modelos não adaptáveis, o que contribui para a melhoria do projeto de agentes autônomos para sistemas multiagente dinâmicos. _______________________________________________________________________________________ ABSTRACTComputational trust and reputation models are key elements in the design of open multi-agent systems. They offer a way of evaluating and reducing risks of cooperation in the presence of uncertainty. However, the models proposed in the literature do not consider the costs they introduce and how they are affected by dynamic environments. In this work, a meta-model for trust and reputation adaptation in dynamic multi-agent systems is proposed. The meta-model acts as a complement to trust and reputation models, by allowing deliberative agents to reason about the components of the model being used, and to react to changes in the environment. The adaptation process is made by adjusting the model's configuration to better ft the current conditions. It is demonstrated how the meta-model can be applied to existing models proposed in the literature, and how adaptation plans can be used to adjust its components dynamically to improve its performance. A learning mechanism, along with a proof of concept implementation based on genetic algorithms, is proposed to identify new adaptation plans for similar scenarios. Finally, the experimental evaluation of the meta-model application and its learning mechanism shows significant improvements in comparison to the use of non-adaptable models. This contributes to improving the design of autonomous agents for dynamic multi-agent systems

Towards trusted volunteer grid environments

Intensive experiences show and confirm that grid environments can be considered as the most promising way to solve several kinds of problems relating either to cooperative work especially where involved collaborators are dispersed geographically or to some very greedy applications which require enough power of computing or/and storage. Such environments can be classified into two categories; first, dedicated grids where the federated computers are solely devoted to a specific work through its end. Second, Volunteer grids where federated computers are not completely devoted to a specific work but instead they can be randomly and intermittently used, at the same time, for any other purpose or they can be connected or disconnected at will by their owners without any prior notification. Each category of grids includes surely several advantages and disadvantages; nevertheless, we think that volunteer grids are very promising and more convenient especially to build a general multipurpose distributed scalable environment. Unfortunately, the big challenge of such environments is, however, security and trust. Indeed, owing to the fact that every federated computer in such an environment can randomly be used at the same time by several users or can be disconnected suddenly, several security problems will automatically arise. In this paper, we propose a novel solution based on identity federation, agent technology and the dynamic enforcement of access control policies that lead to the design and implementation of trusted volunteer grid environments.Comment: 9 Pages, IJCNC Journal 201

Resilient Autonomous Control of Distributed Multi-agent Systems in Contested Environments

An autonomous and resilient controller is proposed for leader-follower multi-agent systems under uncertainties and cyber-physical attacks. The leader is assumed non-autonomous with a nonzero control input, which allows changing the team behavior or mission in response to environmental changes. A resilient learning-based control protocol is presented to find optimal solutions to the synchronization problem in the presence of attacks and system dynamic uncertainties. An observer-based distributed H_infinity controller is first designed to prevent propagating the effects of attacks on sensors and actuators throughout the network, as well as to attenuate the effect of these attacks on the compromised agent itself. Non-homogeneous game algebraic Riccati equations are derived to solve the H_infinity optimal synchronization problem and off-policy reinforcement learning is utilized to learn their solution without requiring any knowledge of the agent's dynamics. A trust-confidence based distributed control protocol is then proposed to mitigate attacks that hijack the entire node and attacks on communication links. A confidence value is defined for each agent based solely on its local evidence. The proposed resilient reinforcement learning algorithm employs the confidence value of each agent to indicate the trustworthiness of its own information and broadcast it to its neighbors to put weights on the data they receive from it during and after learning. If the confidence value of an agent is low, it employs a trust mechanism to identify compromised agents and remove the data it receives from them from the learning process. Simulation results are provided to show the effectiveness of the proposed approach