Publications
255 results found
Gabbay DM, Rodrigues OT, Russo A, 2010, Iterating Revision, Publisher: SPRINGER-VERLAG BERLIN, Pages: 105-137, ISSN: 1611-2482
Gabbay DM, Rodrigues OT, Russo A, 2010, Revision, Acceptability and Context Theoretical and Algorithmic Aspects Conclusions and Discussions, REVISION, ACCEPTABILITY AND CONTEXT: THEORETICAL AND ALGORITHMIC ASPECTS, Publisher: SPRINGER-VERLAG BERLIN, Pages: 359-375, ISBN: 978-3-642-14158-4
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- Citations: 1
Corapi D, Russo A, Lupu E, 2010, INDUCTIVE LOGIC PROGRAMMING AS ABDUCTIVE SEARCH, 26th International Conference on Logic Programming (ICLP), Publisher: SCHLOSS DAGSTUHL, LEIBNIZ CENTER INFORMATICS, Pages: 54-63, ISSN: 1868-8969
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- Citations: 25
Maggi FM, Corapi D, Russo A, et al., 2010, Revising Process Models through Inductive Learning., Publisher: Springer, Pages: 182-193
Hosobe H, Satoh K, Ma J, et al., 2010, Speculative Constraint Processing for Hierarchical Agents, AI Communications: the European journal on artificial intelligence
Ma J, Broda K, Goebel R, et al., 2010, Speculative Abductive Reasoning for Hierarchical Agent Systems, 11th Workshop on Computational Logic in Multi-Agent Systems
Alrajeh D, Ray O, Russo A, et al., 2009, Using Abduction and Induction for Operational Requirements Elaboration, Publisher: Elsevier, Pages: 275-288
Charalambides M, Flegkas P, Pavlou G, et al., 2009, Policy Conflict Analysis for DiffServ Quality of Service Management, IEEE Transactions on Network and Service Management, Vol: 6, Pages: 15-30, ISSN: 1932-4537
Policy-based management provides the ability to (re-)configure differentiated services networks so that desired Quality of Service (QoS) goals are achieved. This requires implementing network provisioning decisions, performing admission control, and adapting bandwidth allocation to emerging traffic demands. A policy-based approach facilitates flexibility and adaptability as policies can be dynamically changed without modifying the underlying implementation. However, inconsistencies may arise in the policy specification. In this paper we provide a comprehensive set of QoS policies for managing Differentiated Services (DiffServ) networks, and classify the possible conflicts that can arise between them. We demonstrate the use of Event Calculus and formal reasoning for the analysis of both static and dynamic conflicts in a semi-automated fashion. In addition, we present a conflict analysis tool that provides network administrators with a user-friendly environment for determining and resolving potential inconsistencies. The tool has been extensively tested with large numbers of policies over a range of conflict types. © 2009 IEEE.
Ma J, Russo A, Broda K, et al., 2009, Multi-agent Planning with Confidentiality, 8th Int. Conf. on Autonomous Agents and Multi-Agent Systems
Craven R, Lobo J, Lupu E, et al., 2009, Security policy refinement using data integration: a position paper., Publisher: ACM, Pages: 25-28
In spite of the wide adoption of policy-based approaches for security management, and many existing treatments of pol- icy verification and analysis, relatively little attention has been paid to policy refinement: the problem of deriving lower-level, runnable policies from higher-level policies, pol- icy goals, and specifications. In this paper we present our initial ideas on this task, using and adapting concepts from data integration. We take a view of policies as governing the performance of an action on a target by a subject, possibly with certain conditions. Transformation rules are applied to these components of a policy in a structured way, in order to translate the policy into more refined terms; the transfor- mation rules we use are similar to those of ‘global-as-view’ database schema mappings, or to extensions thereof. We illustrate our ideas with an example.
Bandara AK, Kakas AC, Lupu EC, et al., 2009, Using Argumentation Logic for Firewall Configuration Management, IFIP/IEEE International Symposium on Integrated Network Management (IM 2009), Publisher: IEEE, Pages: 180-+
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- Citations: 24
Corapi D, Ray O, Russo A, et al., 2009, Learning Rules from User Behaviour, 5th IFIP Conference on Artificial Intelligence Applications and Innovations, Publisher: SPRINGER, Pages: 459-+, ISSN: 1571-5736
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- Citations: 7
Alrajeh D, Kramer J, Russo A, et al., 2009, Learning Operational Requirements from Goal Models, 31st International Conference on Software Engineering, ICSE, ISSN: 0270-5257
Kimber T, Broda K, Russo A, 2009, Induction on Failure: Learning Connected Horn Theories, LPNMR09, Logic Programming and Non-Monotonic Reasoning, Pages: 169-181, ISSN: 0302-9743
Broda K, Clark K, Miller R, et al., 2009, SAGE: A Logical Agent-Based Environment Monitoring and Control System, 3rd European Conf. on Ambient Intelligence
Craven R, Lobo J, Lupu EC, et al., 2009, Expressive Policy Analysis with Enhanced System Dynamicity, ASIAN ACM Symposium on Information, Computer and Communications Security (ASIACCS 09), Publisher: ACM, Pages: 239-250
Gabbay D, Rodrigues O, Russo A, 2008, Belief Revision in Non-classical Logics, The Review of Symbolic Logic Journal, Vol: 1, Pages: 267-304
Dickens L, Broda K, Russo A, 2008, Transparent modelling of finite stochastic processes for multiple agents, Departmental Technical Report: 08/2, Publisher: Department of Computing, Imperial College London, 08/2
Stochastic Processes are ubiquitous, from automated engineering, through financialmarkets, to space exploration. These systems are typically highly dynamic, unpredictableand resistant to analytic methods; coupled with a need to orchestrate long controlsequences which are both highly complex and uncertain. This report examines some existingsingle- and multi-agent modelling frameworks, details their strengths and weaknesses,and uses the experience to identify some fundamental tenets of good practice in modellingstochastic processes. It goes on to develop a new family of frameworks based on these tenets,which can model single- and multi-agent domains with equal clarity and flexibility, whileremaining close enough to the existing frameworks that existing analytic and learning toolscan be applied with little or no adaption. Some simple and larger examples illustrate thesimilarities and differences of this approach, and a discussion of the challenges inherent indeveloping more flexible tools to exploit these new frameworks concludes matters.
Craven R, Lobo J, Lupu E, et al., 2008, A formal framework for policy analysis, Departmental Technical Report: 08/5, Publisher: Department of Computing, Imperial College London, 08/5
We present a formal, logical framework for the representation and analysisof an expressive class of authorization and obligation policies. Basic concepts ofthe language and operational model are given, and details of the representationare defined, with an attention to how different classes of policies can be writtenin our framework. We show how complex dependencies amonst policy rules canbe represented, and illustrate how the formalization of policies is joined to adynamic depiction of system behaviour. Algorithmically, we use a species ofabductive, constraint logic programming to analyse for the holding of a numberof interesting properties of policies (coverage, modality conflict, equivalence ofpolicies, etc.). We describe one implementation of our ideas, and conclude withremarks on related work and future research.
Ma K, Broda K, Clark KL, et al., 2008, DARE: A System for Distributed Abductive REasoning, Journal of Autonomous Agents and Multi-Agent Systems
Alrajeh D, Russo A, Uchitel S, 2008, Deriving non-zeno behavior models from goal models using ILP, 11th International Conference on Fundamental Approaches to Software Engineering, Publisher: SPRINGER-VERLAG BERLIN, Pages: 1-15, ISSN: 0302-9743
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- Citations: 1
Dickens L, Broda K, Russo A, 2008, Modelling MAS as Finite Analytic Stochastic Processes, AISB 2008
Ma J, Broda K, Clark K, et al., 2008, A Dynamic System for Distributed Reasoning, International Symposium on Architectures for Intelligent Theory Based Agents
Bandara A, Lobo J, Calo S, et al., 2007, Toward a Formal Characterization of Policy Specification & Analysis, Annual Conference of ITA (ACITA), Pages: 1-9
Alrajeh D, Ray O, Russo A, et al., 2007, Extracting Requirements from Scenarios using ILP, International Conference on Inductive Logic Programming, Publisher: Springer, Pages: 63-77
Alrajeh D, Ray O, Russo A, et al., 2007, Extracting requirements from scenarios with ILP, 16th International Conference on Inductive Logic Programming, Publisher: SPRINGER-VERLAG BERLIN, Pages: 64-+, ISSN: 0302-9743
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- Citations: 7
Bandara AK, Russo A, Lupu EC, 2007, Towards learning privacy policies, 8th IEEE International Workshop on Policies for Distributed Systems and Networks, Publisher: IEEE COMPUTER SOC, Pages: 274-274
Bandara A, Lupu EC, Russo A, et al., 2006, Policy Refinement for DiffServ Quality of Service Management (2006), 9th IFIP/IEEE Intl. Symp. on Integrated Management (IM 2005), Publisher: IEEE
Alrajeh D, Russo A, Uchitel S, 2006, Inferring Operational Requirements from Scenarios and Goal Models Using Inductive Learning (2006), International Workshop on Scenarios and State Machines: Models, Algorithms, and Tools at the 29th IEEE/ACM International Conference on Software Engineering (ICSE). Shanghai, China, 2003.
Charalambides M, Flegkas P, Pavlou G, et al., 2006, Dynamic Policy Analysis and Conflict Resolution for DiffServ Quality of Service Management (2006), IFIP/IEEE Network Operations and Management Symposium (NOMS 2006), Publisher: IEEE Computer Society
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