A Survey of Moving Target Defenses for Network Security
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by
Sailik Sengupta, Ankur Chowdhary, Abdulhakim Sabur, Adel Alshamrani,
Dijiang Huang, Subbarao Kambhampati
2020
Abstract
Network defenses based on traditional tools, techniques, and procedures fail
to account for the attacker's inherent advantage present due to the static
nature of network services and configurations. To take away this asymmetric
advantage, Moving Target Defense (MTD) continuously shifts the configuration of
the underlying system, in turn reducing the success rate of cyberattacks. In
this survey, we analyze the recent advancements made in the development of MTDs
and define categorizations that capture the key aspects of such defenses. We
first categorize these defenses into different sub-classes depending on what
they move, when they move and how they move. In trying to answer the latter
question, we showcase the use of domain knowledge and game-theoretic modeling
can help the defender come up with effective and efficient movement strategies.
Second, to understand the practicality of these defense methods, we discuss how
various MTDs have been implemented and find that networking technologies such
as Software Defined Networking and Network Function Virtualization act as key
enablers for implementing these dynamic defenses. We then briefly highlight MTD
test-beds and case-studies to aid readers who want to examine or deploy
existing MTD techniques. Third, our survey categorizes proposed MTDs based on
the qualitative and quantitative metrics they utilize to evaluate their
effectiveness in terms of security and performance. We use well-defined metrics
such as risk analysis and performance costs for qualitative evaluation and
metrics based on Confidentiality, Integrity, Availability (CIA), attack
representation, QoS impact, and targeted threat models for quantitative
evaluation. Finally, we show that our categorization of MTDs is effective in
identifying novel research areas and highlight directions for future research.
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