Towards a security event data taxonomy

Gustavo Gonzalez-Granadillo, José Rubio-Hernán, Joaquin Garcia-Alfaro

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The information required to build appropriate impact models depends directly on the nature of the system. The information dealt by health care systems, for instance, is particularly different from the information obtained by energy, telecommunication, transportation, or water supply systems. It is therefore important to properly classify the data of security events according to the nature of the system. This paper proposes an event data classification based on four main aspects: (i) the system’s criticality, i.e., critical vs. non-critical; (ii) the geographical location of the target system, i.e., internal vs. external; (iii) the time at which the information is obtained and used by the attacker i.e., a priory vs. a posteriori; and (iv) the nature of the data, i.e., logical vs. physical. The ultimate goal of the proposed taxonomy is to help organizations in the assessment of their assets and events.

Original languageEnglish
Title of host publicationRisks and Security of Internet and Systems - 12th International Conference, CRiSIS 2017, Revised Selected Papers
EditorsNora Cuppens, Frederic Cuppens, Axel Legay, Jean-Louis Lanet, Joaquin Garcia-Alfaro
PublisherSpringer Verlag
Pages29-45
Number of pages17
ISBN (Print)9783319766867
DOIs
Publication statusPublished - 1 Jan 2018
Externally publishedYes
Event12th International Conference on Risks and Security of Internet and Systems, CRiSIS 2017 - Dinard, France
Duration: 19 Sept 201721 Sept 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10694 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th International Conference on Risks and Security of Internet and Systems, CRiSIS 2017
Country/TerritoryFrance
CityDinard
Period19/09/1721/09/17

Keywords

  • Countermeasure selection
  • Data classification
  • Risk assessment
  • Security event taxonomy

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