Intrusion detection applications using knowledge discovery and data mining
Main Author
Format
Theses
Doctoral thesis
Published
2014
Series
Subjects
ISBN
978-951-39-5978-4
Publisher
University of Jyväskylä
The permanent address of the publication
https://urn.fi/URN:ISBN:978-951-39-5978-4Use this for linking
ISSN
1456-5390
Language
English
Published in
Jyväskylä studies in computing
Contains publications
- Article I: Tuomo Sipola, Antti Juvonen and Joel Lehtonen. Anomaly detection from network logs using diffusion maps. Engineering Applications of Neural Networks, IFIP Advances in Information and Communication Technology, Vol. 363, pp. 172–181, 2011 .Full text
- Article II: Tuomo Sipola, Antti Juvonen and Joel Lehtonen. Dimensionality reduction framework for detecting anomalies from network logs. Engineering Intelligent Systems, Vol. 20, Iss. 1–2, pp. 87–97, 2012. Full text
- Article III: Antti Juvonen and Tuomo Sipola. Adaptive framework for network traffic classification using dimensionality reduction and clustering. Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT), 2012 4th International Congress on, pp. 274–279, 2012. Full text
- Article IV: Mikhail Zolotukhin, Timo Hämäläinen and Antti Juvonen. Growing hierarchical self-organizing maps and statistical distribution models for online detecion of web attacks. Web Information Systems and Technologies. Lecture Notes in Business Information Processing, Vol. 140, pp. 281–295, 2013. DOI: 10.1007/978-3-642-36608-6_18
- Article V: Antti Juvonen and Tuomo Sipola. Combining conjunctive rule extraction with diffusion maps for network intrusion detection. The Eighteenth IEEE Symposium on Computers and Communications (ISCC 2013), pp. 411–416, 2013. Full text.
- Article VI: Antti Juvonen and Timo Hämäläinen. An efficient network log anomaly detection system using random projection dimensionality reduction. New Technologies, Mobility and Security (NTMS), 2014 6th International Conference on, 2014. Full text
- ArticleVII: Antti Juvonen, Tuomo Sipola and Timo Hämäläinen. Online anomaly detection using dimensionality reduction techniques for http log analysis. Submitted to Computer Networks, Elsevier, 2014.