On data mining applications in mobile networking and network security
Published inJyväskylä studies in computing
PublisherUniversity of Jyväskylä
- Article I: Mikhail Zolotukhin, Vesa Hytönen, Timo Hämäläinen and Andrey Garnaev. Optimal Relays Deployment for 802.16j Networks. Springer. Mobile Networks and Management. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Vol. 97, pp. 31–45, 2012. DOI: 10.1080/10.1007/978-3-642-30422-4_3 .
- Article II: Mikhail Zolotukhin, Timo Hämäläinen and Andrey Garnaev. A Relay Deployment Mechanism for One Scenario of Cost-Effective Coverage Extension in IEEE 802.16j Networks. Proceedings of the 5th International Conference on New Technologies, Mobility and Security (NTMS) , pp. 1–6, 2012. DOI: 10.1109/NTMS.2012.6208709
- Article III: Mikhail Zolotukhin, Timo Hämäläinen and Antti Juvonen. Online anomaly detection by using N-gram model and growing hierarchical selforganizing maps. Proceedings of the 8th International Wireless Communications and Mobile Computing Conference (IWCMC) , pp. 47–52, 2012. DOI: 10.1109/IWCMC.2012.6314176 .
- Article IV: Mikhail Zolotukhin, Timo Hämäläinen and Antti Juvonen. Growing Hierarchical Self-organizing Maps and Statistical Distribution Models for Online Detection of Web Attacks. Springer. 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: Mikhail Zolotukhin, Elena Ivannikova and Timo Hämäläinen. Novel Method for the Prediction of Mobile Location Based on Temporal-Spatial Behavioral Patterns. Proceedings of the 3rd IEEE International Conference on Information Science and Technology (ICIST) , pp. 761–766, 2013. DOI: 10.1109/ICIST.2013.6747655 .
- Article VI: Mikhail Zolotukhin and Timo Hämäläinen. Detection of Anomalous HTTP Requests Based on Advanced N-gram Model and Clustering Techniques. Springer. Internet of Things, Smart Spaces, and Next Generation Networking. Lecture Notes in Computer Science , Vol. 8121, pp. 371–382, 2013.DOI: 10.1007/978-3-642-40316-3_33 .
- Article VII: Mikhail Zolotukhin and Timo Hämäläinen. Support Vector Machine Integrated with Game-Theoretic Approach and Genetic Algorithm for the Detection and Classification of Malware. Proceedings of Globecom 2013 Workshop - the 1st International Workshop on Security and Privacy in Big Data, pp. 211–216, 2013. DOI: 10.1109/GLOCOMW.2013.6824988 .
- Article VIII: Mikhail Zolotukhin and Timo Hämäläinen. Detection of Zero-day Malware Based on the Analysis of Opcode Sequences. Proceedings of the 11th Annual IEEE Consumer Communications and Networking Conference (CCNC), pp. 386 - 391, 2014 DOI: 10.1109/CCNC.2014.6866599
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Unsupervised network intrusion detection systems for zero-day fast-spreading network attacks and botnets Vahdani Amoli, Payam (University of Jyväskylä, 2015)Today, the occurrence of zero-day and complex attacks in high-speed networks is increasingly common due to the high number vulnerabilities in the cyber world. As a result, intrusions become more sophisticated and fast ...
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Ivannikova, Elena (University of Jyväskylä, 2017)The subject of this thesis belongs to the topic of machine learning or, speciﬁcally, to the development of advanced methods for regression analysis, clustering, and anomaly detection. Industry is constantly seeking ...
Chen, Tao (University of Jyväskylä, 2014)