Frequency-minimal moving target defense using software-defined networking

Abstract

With the increase of cyber attacks such as DoS, there is a need for intelligent counter-strategies to protect critical cloudhosted applications. The challenge for the defense is to minimize the waste of cloud resources and limit loss of availability, yet have effective proactive and reactive measures that can thwart attackers. In this paper we address the defense needs by leveraging moving target defense protection within SoftwareDefined Networking-enabled cloud infrastructure. Our novelty is in the frequency minimization and consequent location selection of target movement across heterogeneous virtual machines based on attack probability, which in turn minimizes cloud management overheads. We evaluate effectiveness of our scheme using a largescale GENI testbed for a just-in-time news feed application setup. Our results show low attack success rate and higher performance of target application in comparison to the existing static moving target defense schemes that assume homogenous virtual machines.

A Survey of Moving Target Defenses for Network Security

“…Zhu et al [65] Manadhata et al [64] Carter et al [67] Sengupta et al [66], [79] Colbaugh et al [77] Jafarian et al [7] Venkatesan et al [78] Jajodia et al [61] Thompson et al [68] Debroy et al [70] Aydeger et al [58] Clark et al [76] Variable Period Switching An interesting future direction could be to leverage existing security methods that add capabilities to multiple surfaces and see how MTD can be used in conjunction with them. For example, researchers have inspected the techniques involving detection of attacks and countermeasure selection in a single framework called NICE [87].…”

“…Debroy et al [70] utilized GENI framework for implementation of a VM migration MTD solution. The authors utilized the InstaGENI platform at the Illinois site to host a news feed application targeted by DoS attacks.…”

“…[62], [58], [59], [146], [61], [78], [79], [80], [94], [148], [147] [75], [69], [70], [107], [76], [71] [7], [68], [65], [66], [91], [131], [118], [143] Fig . 11: A Moving Target Defense is more effective if it considers the security and performance impacts of the system configurations, both in unison and also when placed in an ensemble of system configurations that the MTD leverages.…”

“…In [69], authors choose an action (to migrate a VM or keep running) after reasoning about the security risks associated with the present vulnerable state. In [70], the security risk is based on the reputation of the current state, which in turn looks at the type and number of attacks that were done in previous time steps when the particular system was deployed. On similar lines, researchers in [65] find a more compact way to model and continuously update the risk associated with deploying a particular defense action.…”

“…Authors in [69] consider the availability of each defense action over a bounded time horizon and for shuffling costs, consider the downtime or unavailability that results when the system is migrating from one system configuration to another. On similar lines, the authors of [70] model the host capacity and network bandwidth associated with each system configuration and also determine the next configuration based on the performance of other defenses in the previous time steps. For some works, the performance costs associated with the ensemble do not arise due to the shuffle but represent the cost of ensuring exact same performance across defense configurations [107] or cost of implementing a system that can support the various configuration [76].…”