Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Aggregate Selection in Multi-objective Biochemical Optimization via the Average Cuboid Volume Indicator Read chapter Read first chapter

2018 | OriginalPaper | Chapter

On Using Cognition for Anomaly Detection in SDN

Authors : Emilia Tantar, Alexandru-Adrian Tantar, Miroslaw Kantor, Thomas Engel

Published in: EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation VI

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Through this position paper we aim at providing a prototype cognitive security service for anomaly detection in Software Defined Networks (SDNs). We equally look at strengthening attack detection capabilities in SDNs, through the addition of predictive analytics capabilities. For this purpose, we build a learning-based anomaly detection service called Learn2Defend, based on functionalities provided by Opendaylight. A potential path to cognition is detailed, by means of a Gaussian Processes driven engine that makes use of traffic characteristics/behavior profiles e.g. smoothness of the frequency of flows traversing a given node. Learn2Defend follows a two-fold approach, with unsupervised learning and prediction mechanisms, all in an on-line dynamic SDN context. The prototype does not target to provide an universally valid predictive analytics framework for security, but rather to offer a tool that supports the integration of cognitive techniques in the SDN security services.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter Parameter Identification of Stochastic Gene Regulation Models by Indicator-Based Evolutionary Level Set Approximation
next chapter Feature Creation Using Genetic Algorithms for Zero False Positive Malware Classification
Literature
1.
Al-Shaer, E., Al-Haj, S.: Flowchecker: configuration analysis and verification of federated openflow infrastructures. In: Sager, T., Ahn, G.-J., Kant, K., Lipford, H.R. (eds.) SafeConfig, pp. 37–44. ACM (2010)
2.
Bishop, C.M.: Pattern recognition and machine learning. In: Information science and statistics. Springer, New York (2006)
3.
Bishop, C.M., Nasrabadi, N.M.: Pattern recognition and machine learning. J. Electron. Imaging 16(4), 049901 (2007)CrossRef
4.
Braga, R., Mota, E., Passito, A.: Lightweight ddos flooding attack detection using nox/openflow. In: IEEE 35th Conference on Local Computer Networks (LCN), 2010, pp. 408–415, Oct 2010
5.
Debar, H., Dacier, M., Wespi, A.: Towards a taxonomy of intrusion-detection systems. Comput. Netw. 31(8), 805–822 (1999)CrossRef
6.
Denning, D.E.: An intrusion-detection model. IEEE Trans. Softw. Eng. 13(2), 222–232 (1987)CrossRef
7.
Erickson, D.: The beacon OpenFlow controller. In: Proceedings of the 2nd ACM SIGCOMM Workshop on Hot Topics in Software Defined Networking, HotSDN 2013, pp. 13–18. ACM, New York (2013)
8.
9.
Genton, M.G.: Classes of kernels for machine learning: a statistics perspective. J. Mach. Learn. Res. 2, 299–312 (2002)MATHMathSciNet
10.
Giotis, K., Argyropoulos, C., Androulidakis, G., Kalogeras, D., Maglaris, V.: Combining openflow and sflow for an effective and scalable anomaly detection and mitigation mechanism on sdn environments. Comput. Netw. 62, 122–136 (2014)CrossRef
11.
Gude, N., Koponen, T., Pettit, J., Pfaff, B., Casado, M., McKeown, N., Shenker, S.: Nox: towards an operating system for networks. SIGCOMM Comput. Commun. Rev. 38(3), 105–110 (2008)CrossRef
12.
Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: The weka data mining software: an update. SIGKDD Explor. Newsl. 11(1), 10–18 (2009)CrossRef
13.
Hand, R., Ton, M., Keller, E.: Active security. In: Proceedings of the Twelfth ACM Workshop on Hot Topics in Networks, HotNets-XII, pp. 17:1–17:7. ACM, New York (2013)
14.
Kreutz, D., Ramos, F.M.V., Veríssimo, P.J.E., Rothenberg, C.E., Azodolmolky, S., Uhlig, S.: Software-defined networking: a comprehensive survey. Proc. IEEE 103(1), 14–76 (2015)CrossRef
15.
Krishnan, R., Krishnaswamy, D., Mcdysan, D.: Behavioral security threat detection strategies for data center switches and routers. In: IEEE 34th International Conference on Distributed Computing Systems Workshops (ICDCSW), 2014, pp. 82–87, June 2014
16.
Kukliński, S., Wytrebowicz, J., Dinh, K.T., Tantar, E.: Application of cognitive techniques to network management and control. In: Tantar, A.-A., et al. (eds.) EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V, pp. 79–93. Springer, Cham (2014)
17.
Matsumoto, S., Hitz, S., Perrig, A.: Fleet: defending sdns from malicious administrators. In: Proceedings of the Third Workshop on Hot Topics in Software Defined Networking, HotSDN 2014, pp. 103–108. ACM, New York (2014)
18.
McKeown, N., Anderson, T., Balakrishnan, H., Parulkar, G., Peterson, L., Rexford, J., Shenker, S., Turner, J.: OpenFlow: enabling innovation in campus networks. In: Proceedings of the ACM SIGCOMM 2008 conference, vol. 38(2), pp. 69–74 (2008)
19.
Mehdi, S.A., Khalid, J., Khayam, S.A.: Revisiting traffic anomaly detection using software defined networking. In: Sommer, R., Balzarotti, D., Maier, G. (eds.) Recent Advances in Intrusion Detection. Lecture Notes in Computer Science, vol. 6961, pp. 161–180. Springer, Heidelberg (2011)CrossRef
20.
21.
22.
23.
24.
Rasmussen, C.E., Williams, C.K.I.: Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning). MIT Press, Cambridge (2005)
25.
Sherwood, R., Gibb, G., Yap, K.-K., Appenzeller, G., Casado, M., McKeown, N., Parulkar, G.: FlowVisor: A Network Virtualization Layer. Technical report , Deutsche Telekom Inc. R&D Lab, Stanford, Nicira Networks (2009)
26.
Sommer, R., Paxson, V.: Outside the closed world: On using machine learning for network intrusion detection. In: IEEE Symposium on Security and Privacy (SP), 2010, pp. 305–316, May 2010
27.
Tantar, E., Palattella, M.R., Avanesov, T., Kantor, M., Engel, T.: Cognition: a tool for reinforcing security in software defined networks. In: Tantar, A.-A., et al. (eds.) EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V, Advances in Intelligent Systems and Computing, vol. 288, pp. 61–78. Springer, Cham (2014)
28.
Yang, L., Dantu, R., Anderson, T.A., Gopal, R.: Forwarding and Control Element Separation (ForCES) Framework, RFC 3746. The Internet Engineering Task Force, April 2004
Metadata
Title
On Using Cognition for Anomaly Detection in SDN
Authors
Emilia Tantar
Alexandru-Adrian Tantar
Miroslaw Kantor
Thomas Engel
Copyright Year
2018
Book
EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation VI

Print ISBN: 978-3-319-69708-6

Electronic ISBN: 978-3-319-69710-9

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-69710-9_5

Premium Partner

    Image Credits