580 research outputs found

    Formal assurance of security policies in automated network orchestration (SDN/NFV)

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    1noL'abstract è presente nell'allegato / the abstract is in the attachmentopen677. INGEGNERIA INFORMATInoopenYusupov, Jalolliddi

    Network Security Automation

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    L'abstract è presente nell'allegato / the abstract is in the attachmen

    An Intelligent Knowledge Management System from a Semantic Perspective

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    Knowledge Management Systems (KMS) are important tools by which organizations can better use information and, more importantly, manage knowledge. Unlike other strategies, knowledge management (KM) is difficult to define because it encompasses a range of concepts, management tasks, technologies, and organizational practices, all of which come under the umbrella of the information management. Semantic approaches allow easier and more efficient training, maintenance, and support knowledge. Current ICT markets are dominated by relational databases and document-centric information technologies, procedural algorithmic programming paradigms, and stack architecture. A key driver of global economic expansion in the coming decade is the build-out of broadband telecommunications and the deployment of intelligent services bundling. This paper introduces the main characteristics of an Intelligent Knowledge Management System as a multiagent system used in a Learning Control Problem (IKMSLCP), from a semantic perspective. We describe an intelligent KM framework, allowing the observer (a human agent) to learn from experience. This framework makes the system dynamic (flexible and adaptable) so it evolves, guaranteeing high levels of stability when performing his domain problem P. To capture by the agent who learn the control knowledge for solving a task-allocation problem, the control expert system uses at any time, an internal fuzzy knowledge model of the (business) process based on the last knowledge model.knowledge management, fuzzy control, semantic technologies, computational intelligence

    A demonstration of VEREFOO: an automated framework for virtual firewall configuration

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    Nowadays, security automation exploits the agility characterizing network virtualization to replace the traditional error-prone human operations. This dynamism allows user-specified high-level intents to be rapidly refined into the concrete configuration rules which should be deployed on virtual security functions. In this revolutionary context, this paper proposes the demonstration of a novel security framework based on an optimized approach for the automatic orchestration of virtual distributed firewalls. The framework provides formal guarantees for the firewall configuration correctness and minimizes the size of the firewall allocation scheme and rule set. The framework produces rules that can be deployed on multiple types of real virtual function implementations, such as iptables, eBPF firewalls and Open vSwitch

    SOME CONCEPTUAL PROPERTIES FOR KNOWLEDGE MANAGEMENT SYSTEMS DESIGN

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    Knowledge Management Systems (KMS) are important tools by which organizations can better useinformation and, more importantly, manage knowledge. Unlike other strategies, knowledge management (KM) isdifficult to define because it encompasses a range of concepts, management tasks, technologies, and organizationalpractices, all of which come under the umbrella of the information management. Semantic approaches alloweasier and more efficient training, maintenance, and support knowledge. Current ICT markets are dominated byrelational databases and document-centric information technologies, procedural algorithmic programmingparadigms, and stack architecture. A key driver of global economic growth in the coming decade is the build-out ofbroadband telecommunications and the deployment of intelligent services bundling. This paper introduces themain characteristics of an Intelligent Knowledge Management System as a multi-agent system used in a LearningControl Problem (IKMSLCP). We describe an intelligent KM framework, allowing the observer (a human agent)to learn from experience
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