Artificial Intelligence & Cybersecurity: A Preliminary Study of Automated Pentesting with Offensive Artificial Intelligence

Marin François, Pierre-Emmanuel Arduin and Myriam Merad (myriam.merad@lamsade.dauphine.fr)
Additional contact information
Marin François: LAMSADE - Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres - CNRS - Centre National de la Recherche Scientifique
Pierre-Emmanuel Arduin: DRM - Dauphine Recherches en Management - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres - CNRS - Centre National de la Recherche Scientifique
Myriam Merad: LAMSADE - Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres - CNRS - Centre National de la Recherche Scientifique

Post-Print from HAL

Abstract: In this paper, we seek to define an experimental framework for the application of a new industrialization method for penetration testing. This work- in-progress research is placed in a particular business context: that of a company with an extensive and decentralized information system. The objective of this research is to give companies the tools to develop a penetration test task force capable of testing any system in a fully automated way and to form proper communication channel and support for risk assessment reporting. It is based on the use of artificial intelligence to make the penetration test autonomous. This research considers the conduct of penetration tests both through their technical issues and through the managerial issues specific to a decentralized information system.

Keywords: Information systems; Penetration-testing; Machine learning; 658.4; Sécurité; espionnage industriel; M15; L86 (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations:

Published in Information and Knowledge Systems. Digital Technologies, Artificial Intelligence and Decision Making, 2021, Virtual Event, France. pp.131-138, ⟨10.1007/978-3-030-85977-0_10⟩

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04712462

DOI: 10.1007/978-3-030-85977-0_10

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD (hal@ccsd.cnrs.fr).