Knowledge Discovery from Network Logs
Sipola, T. (2015). Knowledge Discovery from Network Logs. In M. Lehto, & P. Neittaanmäki (Eds.), Cyber Security: Analytics, Technology and Automation (pp. 195-203). Springer International Publishing. Intelligent Systems, Control and Automation: Science and Engineering, 78. https://doi.org/10.1007/978-3-319-18302-2_12
Julkaistu sarjassa
Intelligent Systems, Control and Automation: Science and EngineeringTekijät
Päivämäärä
2015Tekijänoikeudet
© 2015 Springer
2020:34 | 2021:80 | 2022:45 | 2023:77 | 2024:78 | 2025:6
Modern communications networks are complex systems, which facilitates malicious behavior. Dynamic web services are vulnerable to unknown intrusions, but traditional cyber security measures are based on fingerprinting. Anomaly detection differs from fingerprinting in that it finds events that differ from the baseline traffic. The anomaly detection methodology can be modelled with the knowledge discovery process. Knowledge discovery is a high-level term for the whole process of deriving actionable knowledge from databases. This article presents the theory behind this approach, and showcases research that has produced network log analysis tools and methods.
Julkaisija
Springer International PublishingEmojulkaisun ISBN
978-3-319-18301-5Kuuluu julkaisuun
Cyber Security: Analytics, Technology and AutomationISSN Hae Julkaisufoorumista
2213-8986Asiasanat
Julkaisu tutkimustietojärjestelmässä
https://converis.jyu.fi/converis/portal/detail/Publication/24769601
Metadata
Näytä kaikki kuvailutiedotKokoelmat
Lisenssi
Samankaltainen aineisto
Näytetään aineistoja, joilla on samankaltainen nimeke tai asiasanat.
-
Intrusion detection applications using knowledge discovery and data mining
Juvonen, Antti (University of Jyväskylä, 2014) -
Knowledge discovery using diffusion maps
Sipola, Tuomo (University of Jyväskylä, 2013) -
On Attacking Future 5G Networks with Adversarial Examples : Survey
Zolotukhin, Mikhail; Zhang, Di; Hämäläinen, Timo; Miraghaei, Parsa (MDPI AG, 2023)The introduction of 5G technology along with the exponential growth in connected devices is expected to cause a challenge for the efficient and reliable network resource allocation. Network providers are now required to ... -
Automatic knowledge discovery from sparse and large-scale educational data : case Finland
Saarela, Mirka (University of Jyväskylä, 2017)The Finnish educational system has received a lot of attention during the 21st century. Especially, the outstanding results in the first three cycles of the Programme for International Student Assessment (PISA) have made ... -
Knowledge Discovery from the Programme for International Student Assessment
Saarela, Mirka; Kärkkäinen, Tommi (Springer International Publishing, 2017)The Programme for International Student Assessment (PISA) is a worldwide study that assesses the proficiencies of 15-year-old students in reading, mathematics, and science every three years. Despite the high quality and ...
Ellei toisin mainittu, julkisesti saatavilla olevia JYX-metatietoja (poislukien tiivistelmät) saa vapaasti uudelleenkäyttää CC0-lisenssillä.