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Machine-assisted Cyber Threat Analysis using Conceptual Knowledge Discovery

Identifieur interne : 000436 ( Main/Exploration ); précédent : 000435; suivant : 000437

Machine-assisted Cyber Threat Analysis using Conceptual Knowledge Discovery

Auteurs : Martín Barrère [Royaume-Uni] ; Gustavo Betarte [Uruguay] ; Victor Codocedo [France] ; Marcelo Rodríguez [Uruguay] ; Hernán Astudillo [Chili] ; Marcelo Aliquintuy [Chili] ; Javier Baliosian [Uruguay] ; Rémi Badonnel [France] ; Olivier Festor [France] ; Carlos Raniery Paula Dos Santos [Brésil] ; Jéferson Campos Nobre [Brésil] ; Lisandro Zambenedetti Granville [Brésil] ; Amedeo Napoli [France]

Source :

RBID : Hal:hal-01186213

Abstract

Over the last years, computer networks have evolved into highly dynamic and interconnected environments, involving multiple heterogeneous devices and providing a myriad of services on top of them. This complex landscape has made it extremely difficult for security administrators to keep accurate and be effective in protecting their systems against cyber threats. In this paper, we describe our vision and scientific posture on how artificial intelligence techniques and a smart use of security knowledge may assist system administrators in better defending their networks. To that end, we put forward a research roadmap involving three complimentary axes, namely, (I) the use of FCA-based mechanisms for managing configuration vulnerabilities, (II) the exploitation of knowledge representation techniques for automated security reasoning, and (III) the design of a cyber threat intelligence mechanism as a CKDD process. Then, we describe a machine-assisted process for cyber threat analysis which provides a holistic perspective of how these three research axes are integrated together.

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Le document en format XML

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<div type="abstract" xml:lang="en">Over the last years, computer networks have evolved into highly dynamic and interconnected environments, involving multiple heterogeneous devices and providing a myriad of services on top of them. This complex landscape has made it extremely difficult for security administrators to keep accurate and be effective in protecting their systems against cyber threats. In this paper, we describe our vision and scientific posture on how artificial intelligence techniques and a smart use of security knowledge may assist system administrators in better defending their networks. To that end, we put forward a research roadmap involving three complimentary axes, namely, (I) the use of FCA-based mechanisms for managing configuration vulnerabilities, (II) the exploitation of knowledge representation techniques for automated security reasoning, and (III) the design of a cyber threat intelligence mechanism as a CKDD process. Then, we describe a machine-assisted process for cyber threat analysis which provides a holistic perspective of how these three research axes are integrated together.</div>
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