Tracing CAPEC Attack Patterns from CVE Vulnerability Information using Natural Language Processing Technique

Simple item page
dc.contributor.authorKanakogi, Kenta
dc.contributor.authorWashizaki, Hironori
dc.contributor.authorFukazawa, Yoshiaki
dc.contributor.authorOgata, Shinpei
dc.contributor.authorOkubo , Takao
dc.contributor.authorKato, Takehisa
dc.contributor.authorKanuka, Hideyuki
dc.contributor.authorHazeyama, Atsuo
dc.contributor.authorYoshioka, Nobukazu
dc.date.accessioned2020-12-24T20:27:34Z
dc.date.available2020-12-24T20:27:34Z
dc.date.issued2021-01-05
dc.description.abstractTo effectively respond to vulnerabilities, information must not only be collected efficiently and quickly but also the vulnerability and the attack techniques must be understood. A security knowledge repository can collect such information. The Common Vulnerabilities and Exposures (CVE) provides known vulnerabilities of products, while the Common Attack Pattern Enumeration and Classification (CAPEC) stores attack patterns, which are descriptions of the common attributes and approaches employed by adversaries to exploit known weaknesses. Because the information in these two repositories is not directly related, identifying the related CAPEC attack information from the CVE vulnerability information is challenging. One proposed method traces some related CAPEC-ID from CVE-ID through Common Weakness Enumeration (CWE). However, it is not applicable to all patterns. Here, we propose a method to automatically trace the related CAPEC-IDs from CVE-ID using TF-IDF and Doc2Vec. Additionally, we experimentally confirm that TF-IDF is more accurate than Doc2vec.
dc.format.extent9 pages
dc.identifier.doi10.24251/HICSS.2021.841
dc.identifier.isbn978-0-9981331-4-0
dc.identifier.urihttp://hdl.handle.net/10125/71462
dc.language.isoEnglish
dc.relation.ispartofProceedings of the 54th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectCybersecurity and Software Assurance
dc.subjectcommon attack pattern enumeration and classification
dc.subjectcommon vulnerabilities and exposures
dc.subjectnatural language processing
dc.subjectsecurity
dc.titleTracing CAPEC Attack Patterns from CVE Vulnerability Information using Natural Language Processing Technique
prism.startingpage6996

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
0684.pdf
Size:
1.01 MB
Format:
Adobe Portable Document Format
Download

Collections

Cybersecurity and Software Assurance