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.
Highlights
The generation networking model adopted is the software defined networking (SDN) network architecture which is based on the separation of the network control and configuration logic from the network switching logic, with SDN controllers having a fine-grained control over network routing and reconfiguration [1]
The VISKA security algorithms are designed to run in real time with minimal convergence time for isolating malicious forwarding elements in the data plane
This is the main contribution of the work where malicious switch detection is achieved by an efficient logarithmic divide-and-conquer approach that divides the network view in half in each recursive iteration
Summary
The generation networking model adopted is the SDN network architecture which is based on the separation of the network control and configuration logic from the network switching logic, with SDN controllers having a fine-grained control over network routing and reconfiguration [1]. To provide exact attack categorization and mitigation, a security module scrutinizes live network traffic using data mining and analysis on the real ingress and egress flows of the malicious switch(es) solely rather than inspecting the entire network traffic flows as is the case in traditional intrusion detection systems. This significantly enhances the performance of attack detection and reduces the load on the controller.
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