Evaluating the quantity of incident-related information in an open Cyber security dataset

Benjamin Aziz; John Lee; Gulsum Akkuzu

doi:10.1007/978-3-030-36691-9_45

Evaluating the quantity of incident-related information in an open Cyber security dataset

Benjamin Aziz, John Lee, Gulsum Akkuzu

School of Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

183 Downloads (Pure)

Abstract

Data-driven security has become essential in many organisations in their attempt to tackle Cyber security incidents. However, whilst the dominant approach to data-driven security remains through the mining of private and internal data, there is an increasing trend towards more open data through the sharing of Cyber security information and experience over public and community platforms. However, some questions remain over the quality and quantity of such open data. In this paper, we present the results of a recent case study that considers how feasible it is to answer a common question in Cyber security incident investigations, namely that "in an incident, who did what to which asset or victim, and with what result and impact", for one such open Cyber security database.

Original language	English
Title of host publication	Business Information Systems Workshops. BIS 2019
Editors	Witold Abramowicz, Rafael Corchuelo
Publisher	Springer
Pages	531-542
Number of pages	12
ISBN (Electronic)	978-3-030-36691-9
ISBN (Print)	978-3-030-36690-2
DOIs	https://doi.org/10.1007/978-3-030-36691-9_45
Publication status	Published - 17 Dec 2019
Event	2nd Workshop on Quality of Open Data - Seville, Spain Duration: 26 Jun 2019 → 28 Jun 2019 http://bis.ue.poznan.pl/bis2019/qod/

Publication series

Name	Lecture Notes in Business Information Processing
Publisher	Springer
Volume	373
ISSN (Print)	1865-1348

Workshop

Workshop	2nd Workshop on Quality of Open Data
Abbreviated title	QOD 2019
Country/Territory	Spain
City	Seville
Period	26/06/19 → 28/06/19
Internet address	http://bis.ue.poznan.pl/bis2019/qod/

Keywords

Cyber Security Incidents
Quantity of Information
Open Datasets

Access to Document

10.1007/978-3-030-36691-9_45

Quality_management_in_open_knowledge_bases__BIS_-3
This is a post-peer-review, pre-copyedit version of an article published in Business Information Systems Workshops. BIS 2019. Lecture Notes in Business Information Processing, vol 373. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-030-36691-9_45.
Accepted author manuscript (Post-print), 292 KB

Cite this

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title = "Evaluating the quantity of incident-related information in an open Cyber security dataset",

abstract = "Data-driven security has become essential in many organisations in their attempt to tackle Cyber security incidents. However, whilst the dominant approach to data-driven security remains through the mining of private and internal data, there is an increasing trend towards more open data through the sharing of Cyber security information and experience over public and community platforms. However, some questions remain over the quality and quantity of such open data. In this paper, we present the results of a recent case study that considers how feasible it is to answer a common question in Cyber security incident investigations, namely that {"}in an incident, who did what to which asset or victim, and with what result and impact{"}, for one such open Cyber security database.",

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booktitle = "Business Information Systems Workshops. BIS 2019",

note = "2nd Workshop on Quality of Open Data, QOD 2019 ; Conference date: 26-06-2019 Through 28-06-2019",

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Aziz, B, Lee, J & Akkuzu, G 2019, Evaluating the quantity of incident-related information in an open Cyber security dataset. in W Abramowicz & R Corchuelo (eds), Business Information Systems Workshops. BIS 2019. Lecture Notes in Business Information Processing, vol. 373, Springer, pp. 531-542, 2nd Workshop on Quality of Open Data, Seville, Spain, 26/06/19. https://doi.org/10.1007/978-3-030-36691-9_45

Evaluating the quantity of incident-related information in an open Cyber security dataset. / Aziz, Benjamin; Lee, John; Akkuzu, Gulsum.
Business Information Systems Workshops. BIS 2019. ed. / Witold Abramowicz; Rafael Corchuelo. Springer, 2019. p. 531-542 ( Lecture Notes in Business Information Processing; Vol. 373).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Evaluating the quantity of incident-related information in an open Cyber security dataset

Abstract

Publication series

Workshop

Keywords

Access to Document

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Cite this