Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/57059
Title: Attack Detection on the Software Defined Networking Switches
Contributor(s): Tupakula, Udaya  (author)orcid ; Varadharajan, Vijay (author); Karmakar, Kallol Krishna (author)
Publication Date: 2020
DOI: 10.1109/netsoft48620.2020.9165459
Handle Link: https://hdl.handle.net/1959.11/57059
Abstract: 

Software Defined Networking (SDN) is disruptive networking technology which adopts a centralised framework to facilitate fine-grained network management. However security in SDN is still in its infancy and there is need for significant work to deal with different attacks in SDN. In this paper we discuss some of the possible attacks on SDN switches and propose techniques for detecting the attacks on switches. We have developed a Switch Security Application (SSA)for SDN Controller which makes use of trusted computing technology and some additional components for detecting attacks on the switches. In particular TPM attestation is used to ensure that switches are in trusted state during boot time before configuring the flow rules on the switches. The additional components are used for storing and validating messages related to the flow rule configuration of the switches. The stored information is used for generating a trusted report on the expected flow rules in the switches and using this information for validating the flow rules that are actually enforced in the switches. If there is any variation to flow rules that are enforced in the switches compared to the expected flow rules by the SSA, then, the switch is considered to be under attack and an alert is raised to the SDN Administrator. The administrator can isolate the switch from network or make use of trusted report for restoring the flow rules in the switches. We will also present a prototype implementation of our technique.

Publication Type: Conference Publication
Conference Details: 2020 6th IEEE Conference on Network Softwarization (NetSoft), Ghent, Belgium, 29th June - 3rd July, 2020
Source of Publication: Proceedings of the 2020 IEEE Conference on Network Softwarization : NetSoft 2020 : Bridging the gap between AI and network softwarization, p. 262-266, p. 262-266
Publisher: IEEE
Place of Publication: Piscataway, New Jersey, United States of America
Fields of Research (FoR) 2020: 460407 System and network security
Socio-Economic Objective (SEO) 2020: 220405 Cybersecurity
Peer Reviewed: Yes
HERDC Category Description: E1 Refereed Scholarly Conference Publication
Appears in Collections:Conference Publication
School of Science and Technology

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