A4 Article in conference proceedings
Utilizing Vector Database Management Systems in Cyber Security (2024)


Taipalus, T., Grahn, H., Turtiainen, H., & Costin, A. (2024). Utilizing Vector Database Management Systems in Cyber Security. In M. Lehto (Ed.), Proceedings of the 23rd European Conference on Cyber Warfare and Security (23, pp. 560-565). Academic Conferences International Ltd. Proceedings of the European Conference on Cyber Warfare and Security. https://doi.org/10.34190/eccws.23.1.2220


JYU authors or editors


Publication details

All authors or editorsTaipalus, Toni; Grahn, Hilkka; Turtiainen, Hannu; Costin, Andrei

Parent publicationProceedings of the 23rd European Conference on Cyber Warfare and Security

Parent publication editorsLehto, Martti

Conference:

  • European Conference on Cyber Warfare and Security

Place and date of conferenceJyväskylä, Finland27.-28.6.2024

Journal or seriesProceedings of the European Conference on Cyber Warfare and Security

ISSN2048-8602

eISSN2048-8610

Publication year2024

Publication date21/06/2024

Volume23

Issue number1

Pages range560-565

Number of pages in the book847

PublisherAcademic Conferences International Ltd

Publication countryUnited Kingdom

Publication languageEnglish

DOIhttps://doi.org/10.34190/eccws.23.1.2220

Persistent website addresshttps://papers.academic-conferences.org/index.php/eccws/issue/view/33

Publication open accessOpenly available

Publication channel open accessOpen Access channel

Publication is parallel published (JYX)https://jyx.jyu.fi/handle/123456789/96213


Abstract

The rising popularity of phenomena such as ubiquitous computing and IoT poses increasingly high demands for data management, and it is not uncommon that database management systems (DBMS) must be capable of reading and writing hundreds of operations per second. Vector DBMSs (VDBMS) are novel products that focus on the management of vector data and can alleviate data management pressures by storing data objects such as logs, system calls, emails, network flow data, and memory dumps in feature vectors that are computationally efficient in both storage and information retrieval. VDMBSs allow efficient nearest neighbour similarity search on complex data objects, which can be used in various cyber security applications such as anomaly, intrusion, malware detection, user behaviour analysis, and network flow analysis. This study describes VDBMSs and some of their use cases in cyber security.


Keywordscyber securitydata securityphishing

Free keywordsvector database; anomaly detection; traffic analysis; cyber security; phishing detection


Contributing organizations


Ministry reportingYes

Reporting Year2024

Preliminary JUFO rating1


Last updated on 2024-17-07 at 14:53