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Intelligent Agents Organisation to Enhance Dependability and Survivability of Large Complex Critical Infrastructure

Ziel

SAFEGUARD aims to enhance the dependability and survivability of Large Complex Critical Infrastructures (LCCIs), such as distributed electric and telecommunication networks. Modern automation systems underlying LCCIs include different levels of automation, regulation, and control, but "intelligent" functions relating to critical issues such as system dependability and survivability are usually monitored or executed by human operators. SAFEGUARD will improve dependability and survivability of large infrastructures as perceived by all interested parties: the owners, operators and customers. The main objective of the project is to provide a systemic conceptual framework and an integrated software toolkit that, employed within an intelligent multi-agent system, enhance the dependability and survivability of Large Complex Critical Infrastructures (LCCIs). SAFEGUARD aims to enhance the dependability and survivability of Large Complex Critical Infrastructures (LCCIs), such as distributed electric and telecommunication networks. Modern automation systems underlying LCCIs include different levels of automation, regulation, and control, but "intelligent" functions relating to critical issues such as system dependability and survivability are usually monitored or executed by human operators. SAFEGUARD will improve dependability and survivability of large infrastructures as perceived by all interested parties: the owners, operators and customers. The main objective of the project is to provide a systemic conceptual framework and an integrated software toolkit that, employed within an intelligent multi-agent system, enhance the dependability and survivability of Large Complex Critical Infrastructures (LCCIs).

OBJECTIVES
The main objective is to provide a systemic conceptual framework and software tools (integrated methodologies, models, methods and middleware). As part of a multi-agent system, the dependability and survivability of Large Complex Critical Infrastructures (LCCIs) is enhanced. The scientific objective is to validate the applicability and efficacy of an intelligent agent organisation (and to develop related methodologies and methods) in support of LCCIs for ensuring their dependability and survivability. Technological objectives will be the development of middleware for software agent components and their integration, applied to our domain of interest.

DESCRIPTION OF WORK
SAFEGUARD will enhance the dependability and survivability of Large Complex Critical Infrastructures (LCCIs), such as distributed electricity and telecommunication networks. Modern automation systems underlying LCCIs include different levels of automation, regulation, and control, but "intelligent" functions relating to critical issues such as safety and system survivability are usually monitored or executed by human operators. SAFEGUARD will improve dependability and survivability of large infrastructures as perceived by all interested parties: the owners, operators and customers. An organisation of "Safeguards" is proposed. This has the role of an internal system supervisor including an auto-defence against different intrusions (for example hacking). Here, the main goal is to avoid unexpected widespread network failures and infrastructure disasters. Individual Safeguards should learn roles, responsibilities, duties and data access capabilities; they should accept tasks and evolve and adapt to the changing environment and in so doing, improve their capabilities. The domain of interest can be represented by three layers: 1) the physical infrastructure; 2) automation and control; 3) supervision and management. The project will introduce an intelligent SAFEGUARD layer between the second and the third layer, in order to introduce new survivability functions and to implement into computer systems some of those being implemented, at present, by humans. As a test case an organisation of Safeguards will be constructed for each of the validation scenarios and the constructed system validated on testbeds.

MILESTONES


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QUEEN MARY AND WESTFIELD COLLEGE, UNIVERSITY OF LONDON
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E1 4NS LONDON
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Beteiligte (4)

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