Probabilistic Transition-Based Approach for Detecting Application-Layer DDoS Attacks in Encrypted Software-Defined Networks
Ivannikova, E., Zolotukhin, M., & Hämäläinen, T. (2017). Probabilistic Transition-Based Approach for Detecting Application-Layer DDoS Attacks in Encrypted Software-Defined Networks. In Z. Yan, R. Molva, W. Mazurczyk, & R. Kantola (Eds.), Network and System Security : 11th International Conference, NSS 2017 Helsinki, Finland, August 21–23, 2017, Proceedings (pp. 531-543). Springer. Lecture Notes in Computer Science, 10394. https://doi.org/10.1007/978-3-319-64701-2_40
Published in
Lecture Notes in Computer ScienceDate
2017Copyright
© Springer International Publishing AG 2017. This is a final draft version of an article whose final and definitive form has been published by Springer. Published in this repository with the kind permission of the publisher.
With the emergence of cloud computing, many attacks, including Distributed Denial-of-Service (DDoS) attacks, have changed their direction towards cloud environment. In particular, DDoS attacks have changed in scale, methods, and targets and become more complex by using advantages provided by cloud computing. Modern cloud computing environments can benefit from moving towards Software-Defined Networking (SDN) technology, which allows network engineers and administrators to respond quickly to the changing business requirements. In this paper, we propose an approach for detecting application-layer DDoS attacks in cloud environment with SDN. The algorithm is applied to statistics extracted from network flows and, therefore, is suitable for detecting attacks that utilize encrypted protocols. The proposed detection approach is comprised of the extraction of normal user behavior patterns and detection of anomalies that significantly deviate from these patterns. The algorithm is evaluated using DDoS detection system prototype. Simulation results show that intermediate application-layer DDoS attacks can be properly detected, while the number of false alarms remains low.
...
Publisher
SpringerParent publication ISBN
978-3-319-64700-5Conference
International Conference on Network and System SecurityIs part of publication
Network and System Security : 11th International Conference, NSS 2017 Helsinki, Finland, August 21–23, 2017, ProceedingsISSN Search the Publication Forum
0302-9743Publication in research information system
https://converis.jyu.fi/converis/portal/detail/Publication/27211915
Metadata
Show full item recordCollections
License
Related items
Showing items with similar title or keywords.
-
On Application-Layer DDoS Attack Detection in High-Speed Encrypted Networks
Zolotukhin, Mikhail; Kokkonen, Tero; Hämäläinen, Timo; Siltanen, Jarmo (Advanced Institute of Convergence IT, 2016)Application-layer denial-of-service attacks have become a serious threat to modern high-speed computer networks and systems. Unlike network-layer attacks, application-layer attacks can be performed by using legitimate ... -
Detection of distributed denial-of-service attacks in encrypted network traffic
Hyvärinen, Mikko (2016)Tausta: Hajautetut palvelunestohyökkäykset ovat jo kaksi vuosikymmentä vanhoja. Useita strategioita on kehitetty taistelemaan niiden kasvavaa määrää vastaan vuosien varrella. Sovelluskerroksen protokollien hyökkäykset ... -
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 ... -
Software-defined networking, current state, applicability and security
Ylitalo, Waltteri (2024)This thesis performs a descriptive literature review on software-defined networking. SD-networks are a new software-based networking approach where the control and data transmission mechanisms are separated. This separation ... -
Anomaly Detection and Classification of Household Electricity Data : A Time Window and Multilayer Hierarchical Network Approach
Zhao, Qiang; Chang, Zheng; Min, Geyong (Institute of Electrical and Electronics Engineers (IEEE), 2022)With the increasing popularity of the smart grid, huge volumes of data are gathered from numerous sensors. How to classify, store, and analyze massive datasets to facilitate the development of the smart grid has recently ...