Abstract
Application Layer DDoS (AL-DDoS) is a major danger for Internet information services, because these attacks are easily performed and implemented by attackers and are difficult to detect and stop using traditional firewalls. Managing to saturate physically and computationally the information services offered on the network. Directly harming legitimate users, to deal with this type of attacks in the network layer previous approaches propose to use a configurable statistical model and observed that when being optimized in various configuration parameters Using Genetic Algorithms was able to optimize the effectiveness to detect Network Layer DDoS (NL-DDoS), however this method is not enough to stop DDoS at the level of application because this level presents different characteristics, that is why we propose a new method Configurable and optimized for different scenarios of Attacks that effectively detect AL-DDoS.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Application-layer denial of service (2011). http://forums.juniper.net/t5/Security-Mobility-Now/Application-layer-Denial-of-Service/ba-p/103306
Using Human Behavioral Analysis to Stop DDOS at Layer 7 (2012). http://hwww.networkcomputing.com/security/using-human-behavioral-analysis-to-stop/240007110
Kim, T.H., Kim, D.S., Lee, S.M., Park, J.S.: Detecting DDoS attacks using dispersible traffic matrix and weighted moving average. In: Park, J.H., Chen, H.-H., Atiquzzaman, M., Lee, C., Kim, T., Yeo, S.-S. (eds.) ISA 2009. LNCS, vol. 5576, pp. 290–300. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-02617-1_30
Lee, S.M., Kim, D.S., Lee, J.H., Park, J.S.: Detection of DDoS attacks using optimized traffic matrix. Comput. Math. Appl. 63(2), 501–510 (2012)
Prabha, S., Anitha, R.: Mitigation of application traffic DDoS attacks with trust and AM based HMM models. Int. J. Comput. Appl. IJCA 6(9), 26–34 (2010)
Bottomley, L., Balbach, S., Arlitt, M., Williamson, C.: The Internet Traffic Archive (2000). http://ita.ee.lbl.gov/EPA-HTTPNASA-HTTPClarkNet-HTTP
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Quequezana-Buendia, J., Santisteban, J. (2018). AL-DDoS Attack Detection Optimized with Genetic Algorithms. In: Castro, F., Miranda-Jiménez, S., González-Mendoza, M. (eds) Advances in Soft Computing. MICAI 2017. Lecture Notes in Computer Science(), vol 10632. Springer, Cham. https://doi.org/10.1007/978-3-030-02837-4_9
Download citation
DOI: https://doi.org/10.1007/978-3-030-02837-4_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-02836-7
Online ISBN: 978-3-030-02837-4
eBook Packages: Computer ScienceComputer Science (R0)