kth.sePublications KTH
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Time between vulnerability disclosures: A measure of software product vulnerability
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.ORCID iD: 0000-0002-3293-1681
Foreseeti, Stockholm, Sweden.
KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.ORCID iD: 0000-0003-3089-3885
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.ORCID iD: 0000-0003-3922-9606
2016 (English)In: Computers & Security, ISSN 0167-4048, E-ISSN 1872-6208, Vol. 62, p. 278-295Article in journal (Refereed) Published
Abstract [en]

Time between vulnerability disclosure (TBVD) for individual analysts is proposed as a meaningful measure of the likelihood of finding a zero-day vulnerability within a given timeframe. Based on publicly available data, probabilistic estimates of the TBVD of various software products are provided. Sixty-nine thousand six hundred forty-six vulnerabilities from the National Vulnerability Database (NVD) and the SecurityFocus Vulnerability Database were harvested, integrated and categorized according to the analysts responsible for their disclosure as well as by the affected software products. Probability distributions were fitted to the TBVD per analyst and product. Among competing distributions, the Gamma distribution demonstrated the best fit, with the shape parameter, k, similar for most products and analysts, while the scale parameter, 8, differed significantly. For forecasting, autoregressive models of the first order were fitted to the TBVD time series for various products. Evaluation demonstrated that forecasting of TBVD on a per product basis was feasible. Products were also characterized by their relative susceptibility to vulnerabilities with impact on confidentiality, integrity and availability respectively. The differences in TBVD between products is significant, e.g. spanning differences of over 500% among the 20 most common software products in our data. Differences are further accentuated by the differing impact, so that, e.g., the mean working time between disclosure of vulnerabilities with a complete impact on integrity (as defined by the Common Vulnerability Scoring System) for Linux (110 days) exceeds that of Windows 7 (6 days) by over 18 times.

Place, publisher, year, edition, pages
Elsevier, 2016. Vol. 62, p. 278-295
Keywords [en]
Software vulnerability, Time between vulnerability disclosures, Distribution fitting, Time series analysis, Information security, Cyber security
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-196623DOI: 10.1016/j.cose.2016.08.004ISI: 000386408600017Scopus ID: 2-s2.0-84983756963OAI: oai:DiVA.org:kth-196623DiVA, id: diva2:1047378
Funder
EU, FP7, Seventh Framework Programme, 607109
Note

QC 20161117. QC 20191023

Available from: 2016-11-17 Created: 2016-11-17 Last updated: 2025-08-28Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Johnson, PontusLagerström, RobertEkstedt, Mathias

Search in DiVA

By author/editor
Johnson, PontusLagerström, RobertEkstedt, Mathias
By organisation
Electric Power and Energy SystemsIndustrial Information and Control Systems
In the same journal
Computers & Security
Computer and Information Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 666 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf