Proactive routing mutation against stealthy Distributed Denial of Service attacks: metrics, modeling, and analysis

Author:

Duan Qi1,Al-Shaer Ehab1,Chatterjee Samrat2,Halappanavar Mahantesh2,Oehmen Christopher2

Affiliation:

1. Cyber Defense and Network Assurability Center, College of Computing and Informatics, University of North Carolina Charlotte, USA

2. Pacific Northwest National Laboratory, USA

Abstract

Infrastructure Distributed Denial of Service (IDDoS) attacks continue to be one of the most devastating challenges facing cyber systems. The new generation of IDDoS attacks exploits the inherent weakness of cyber infrastructure, including the deterministic nature of routing, skewed distribution of flows, and Internet ossification to discover the network critical links and launch highly stealthy flooding attacks that are not observable at the victim’s end. In this paper, first, we propose a new metric to quantitatively measure the potential susceptibility of any arbitrary target server or domain to stealthy IDDoS attacks, and estimate the impact of such susceptibility on enterprises. Second, we develop proactive route mutation techniques to minimize the susceptibility to these attacks by dynamically changing the flow paths periodically to invalidate the adversary knowledge about the network and avoid targeted critical links. Our proposed approach actively changes these network paths while satisfying security and Quality of Service requirements. We implemented the proactive path mutation technique on a Software Defined Network using the OpenDaylight controller to demonstrate a feasible deployment of this approach. Our evaluation validates the correctness, effectiveness, and scalability of the proposed approaches.

Publisher

SAGE Publications

Subject

Engineering (miscellaneous),Modeling and Simulation

Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Prevention of DDoS attacks: a comprehensive review and future directions;Information Security Journal: A Global Perspective;2024-05-15

2. Autonomous Cyber Defense Against Dynamic Multi-strategy Infrastructural DDoS Attacks;2023 IEEE Conference on Communications and Network Security (CNS);2023-10-02

3. Toward Attack-Resistant Route Mutation for VANETs: An Online and Adaptive Multiagent Reinforcement Learning Approach;IEEE Transactions on Intelligent Transportation Systems;2022-12

4. A Hybrid Routing Mutation Mechanism based on Mutation Cost and Resource Trustworthiness in Network Moving Target Defense;2022 7th IEEE International Conference on Data Science in Cyberspace (DSC);2022-07

5. Moving target defense of routing randomization with deep reinforcement learning against eavesdropping attack;Digital Communications and Networks;2022-06

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