Network Programming and Probabilistic Sketching for Securing the Data Plane. (28th June 2018)

• Record Type: Journal Article
• Authors: Shamseddine, Maha; Itani, Wassim; Chehab, Ali; Kayssi, Ayman
• Other Names: Di Pietro Roberto Academic Editor.
• Is Part Of: Security and communication networks. Volume 2018(2018)
• Publication Date: 2018-06-28
• Subjects: Computer networks -- Security measures -- Periodicals; Computer security -- Periodicals; Cryptography -- Periodicals; 005.805
• DOI: 10.1155/2018/2905730
• Languages: English
• ISSNs: 1939-0114

Abstract

Abstract : This paper presents VISKA, a cloud security service for dynamically detecting malicious switching elements in software defined networking (SDN) infrastructures. The main contributions of VISKA lie in (1) utilizing network programming and secure probabilistic sketching in SDN environments to dynamically detect and isolate parts of the data plane that experience malicious behavior, (2) applying a set of focused packet probing and sketching mechanisms on isolated network partitions/views rather than focusing the security mechanisms on the whole physical network, (3) efficiently analyzing the network behavior of the resulting views by recursively partitioning them in a divide-and-conquer fashion to logarithmically reduce the problem size in order to localize abnormal/malicious switching units, and (4) providing an attack categorization module that analyzes live ingress/egress traffic of the maliciously detected switch(es) solely to identify the specific type of attack, rather than inspecting the whole network traffic as is done in traditional intrusion detection systems. This significantly enhances the performance of attack detection and reduces the load on the controller. A testbed prototype implementation is realized on the Mininet network emulator. The experimental analysis corroborated the algorithms' convergence property using the linear and FatTree topologies with network sizes of up to 250 switches. Moreover, an implementation of the attack categorization module is realized and achieved an accuracy rate of over 90% for the different attack types supported.