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Reference: Janse van Rensburg, A, Nurse, JRC and Goldsmith, M, (2016). Attacker-parametrised attack graphs.Citable link to this page:

 

Attacker-parametrised attack graphs

Abstract: Computer network attackers chain system exploits together to achieve their goals, which range from stealing data to corrupting systems. Attack graphs represent these paths through the network, and provide the basis for calculating many security metrics. In this paper, we seek to extend graph-based analysis from the consideration of single graphs to the consideration of multiple. By performing analysis on many graphs at once, we consider the range of threats faced and avoid the downsides of several current techniques, which focus purely on known and expected attackers. In particular, we propose a novel method of generating a set of attack graphs, parametrised by attacker profiles. Our technique would enable security analysts to consider the security of their network from the perspective of many attackers simultaneously. This contrasts with existing techniques, which typically analyse attacker-independent graphs or graphs constructed around predefined attacker profiles. We analyse the resulting set of graphs first through deterministic methods and then using a probability measure.

Publication status:PublishedPeer Review status:Peer reviewedVersion:Accepted manuscriptNotes:Copyright (c) IARIA, 2016. IARIA grants royalty-free permission to the authors to disseminate the work, under the above provisions, for any academic, commercial, or industrial use. IARIA grants royalty-free permission to any individuals or institutions to make the article available electronically, online, or in print.

Bibliographic Details

Publisher: ThinkMind Digital Library

Publisher Website: http://www.thinkmind.org/

Host: Tenth International Conference on Quantum, Nano/Bio, and Micro Technologies (ICQNM 2016)see more from them

Publication Website: http://www.iaria.org/conferences2016/ProgramICQNM16.html

Issue Date: 2016-07Identifiers

Uuid: b156c235-d097-4ba4-bd5a-927833f02ea0

Urn: uri:b156c235-d097-4ba4-bd5a-927833f02ea0

Pubs-id: pubs:637379 Item Description

Type: conference-proceeding;

Version: Accepted manuscriptKeywords: Attack Graphs Attacker Profiling Intrusion Detection

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Author: Janse van Rensburg, A - Oxford, MPLS, Computer Science - - - Nurse, JRC - Oxford, MPLS, Computer Science - - - Goldsmith, M - Oxf

Source: https://ora.ox.ac.uk/objects/uuid:b156c235-d097-4ba4-bd5a-927833f02ea0



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