A4 Article in conference proceedings
A Novel Method for Detecting APT Attacks by Using OODA Loop and Black Swan Theory (2018)


Bodström, T., & Hämäläinen, T. (2018). A Novel Method for Detecting APT Attacks by Using OODA Loop and Black Swan Theory. In X. Chen, A. Sen, W. W. Li, & M. T. Thai (Eds.), Computational Data and Social Networks : 7th International Conference, CSoNet 2018, December 18-20, 2018, Shanghai, China, Proceedings (pp. 498-509). Cham: Springer. doi:10.1007/978-3-030-04648-4_42


JYU authors or editors


Publication details

All authors or editors: Bodström, Tero; Hämäläinen, Timo

Parent publication: Computational Data and Social Networks : 7th International Conference, CSoNet 2018, December 18-20, 2018, Shanghai, China, Proceedings

Parent publication editors: Chen, Xuemin; Sen, Arunabha; Li, Wei Wayne; Thai, My T.

Conference:

  • International Conference on Computational Social Networks

ISBN: 978-3-030-04647-7

Journal or series: Lecture Notes in Computer Science

ISSN: 0302-9743

Publication year: 2018

Number in series: 11280

Pages range: 498-509

Number of pages in the book: 544

Publisher: Springer

Place of Publication: Cham

Publication country: Switzerland

Publication language: English

DOI: https://doi.org/10.1007/978-3-030-04648-4_42

Open Access: Publication channel is not openly available

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/60675

Additional information: The 7th International Conference on Computational Data & Social Networks (CSoNet 2018) December 18-20, 2018, Shanghai, China


Free keywords: Advanced Persistent Thread (APT); OODA loop; Black Swan theory; network anomaly detection


Contributing organizations


Ministry reporting: Yes

Reporting Year: 2018

JUFO rating: 0


Last updated on 2020-18-10 at 20:26