How to Mitigate DDoS Intelligently in SD-IoV: A Moving Target Defense Approach

Zhang, Tao; Xu, Changqiao; Zou, Ping; Hai-jiang, Tian; Kuang, Xiaohui; Yang, Shujie; Zhong, Lujie; Niyato, Dusit

doi:10.1109/tii.2022.3190556

Cited by 42 publications

(21 citation statements)

References 42 publications

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“…Several trust-based defense mechanisms for DDoS attacks in VANET [ 43 , 44 , 45 ] rely on the trust score of neighboring vehicles. These studies propose fixed and learning-based trust mechanisms for different VANET scenarios.…”

Section: Related Workmentioning

confidence: 99%

RSU-Based Online Intrusion Detection and Mitigation for VANET

Haydari

Yılmaz

2022

Sensors

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Secure vehicular communication is a critical factor for secure traffic management. Effective security in intelligent transportation systems (ITS) requires effective and timely intrusion detection systems (IDS). In this paper, we consider false data injection attacks and distributed denial-of-service (DDoS) attacks, especially the stealthy DDoS attacks, targeting integrity and availability, respectively, in vehicular ad-hoc networks (VANET). Novel machine learning techniques for intrusion detection and mitigation based on centralized communications through roadside units (RSU) are proposed for the considered attacks. The performance of the proposed methods is evaluated using a traffic simulator and a real traffic dataset. Comparisons with the state-of-the-art solutions clearly demonstrate the superior detection and localization performance of the proposed methods by 78% in the best case and 27% in the worst case, while achieving the same level of false alarm probability.

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Section: Related Workmentioning

confidence: 99%

RSU-Based Online Intrusion Detection and Mitigation for VANET

Haydari

Yılmaz

2022

Sensors

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“…Te mutation is realized by the multi-agent reinforcement learning based on the observation of nodes in the Markov process. Meanwhile, Zhang et al proposed an intelligent defense scheme against DDoS in the software-defned Internet of vehicles in VANET [38]. Te scheme periodically mutates the network communication range and access capacity of the road side units based on deep reinforcement learning.…”

Section: Mtdmentioning

confidence: 99%

“…However, those solutions have insufciency in defense against the crossfre attack as follows. (a) Defenses in VANET [37,38] are designed based on ad hoc routes that are suitable for general networks. (b) Te solutions [36][37][38] have not mentioned how to identify the links or hosts under attack.…”

Section: Mtdmentioning

confidence: 99%

“…(a) Defenses in VANET [37,38] are designed based on ad hoc routes that are suitable for general networks. (b) Te solutions [36][37][38] have not mentioned how to identify the links or hosts under attack. (c) For all of them [36][37][38], fnding the link-disjoint path or the route mutation is impossible for the critical PRs in general networks.…”

Section: Mtdmentioning

confidence: 99%

“…(b) Te solutions [36][37][38] have not mentioned how to identify the links or hosts under attack. (c) For all of them [36][37][38], fnding the link-disjoint path or the route mutation is impossible for the critical PRs in general networks. Later, Gupta et al developed a defense mechanism to change interdomain paths and performed address hopping for setting up a honey pot [13].…”

Section: Mtdmentioning

confidence: 99%

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A Persistent Route Diversification Mechanism for Defending against Stealthy Crossfire Attack

Zhou

Yang

et al. 2022

Security and Communication Networks

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Computer networks are facing the challenge of stealthy crossfire attacks that flood through persistent routes (PRs) towards their decoys at a low rate for disrupting end-to-end connectivity of the target. At first, the PRs can be stealthily probed at the initial stage of the attack. Later, some undefended and vulnerable PRs can be speculated at the renaissance stage of the attack, which yet remains unconcerned. To achieve an effective defense against the two-stage attacks, this paper investigates a new persistent route diversification defense (PRDD) mechanism to mitigate each identified PR under the attacks. The PRDD effectively stops the flooding on the PRs to mitigate their congestion. Meanwhile, it makes the adversary unable to probe or speculate the PRs under their corresponding attack stages. Thus, it disables every flooding choice for the adversary, avoiding the attacks. The PRDD is designed with scalable algorithmic complexity in computation and overhead. The PRDD is extensively assessed using NS-3 and Mininet, and the results show the following. (a) It is more effective in mitigating more attacked PRs compared with the existing solutions. (b) The defense performance of the PRDD remains highly scalable in computation, while maintaining an acceptable overhead.

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Blockchain‐enhanced trust management for mobile edge computing‐enabled intelligent vehicular collaboration in the 6G era

Wang

Zhu

Xiao

et al. 2023

Trans Emerging Tel Tech

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The rapid development and increasing popularity of mobile devices have facilitated the development of computation‐intensive applications and services, but their constrained compute, storage and battery capabilities have also created the requirements for optimized resource provision and service orchestration. Emerging mobile edge computing (MEC) and next‐generation networks (6G) can meet these requirements of mobile devices by migrating complex computing tasks and large volumes of data to edge servers with acceptable latency, thus effectively enhancing the quality of experience (QoE) of mobile users. Intelligent Vehicular Collaboration, as an intelligent mobile application or service in intelligent connected vehicle (ICV) applications, enables precise and effective driving decisions based on a large amount of real‐time traffic information statistics and intelligent analysis of vehicle status to improve the user driving experience and the efficiency of intelligent transportation systems(ITS). However, the openness and dynamics of wireless communications and the high frequency of information interaction of MEC‐enabled intelligent vehicular collaboration services in the 6G era make them highly vulnerable to cyber attacks. How to achieve dynamically trustworthy, secure, and intelligent vehicular collaboration services in the presence of malicious node access and cyber attacks in the 6G MEC‐enabled vehicular network is a significant challenge. In this paper, we propose a novel blockchain‐enabled trust management mechanism to address this challenge. First, we design a spatiotemporal‐correlated message credibility assessment method and a dynamic mutual trust evaluation method to obtain accurate ratings for messages and mobile nodes respectively. Based on the above methods, we propose an improved blockchain‐based intelligent trust management mechanism that enables transparent, tamper‐evident, and trustworthy secure intelligent vehicular collaboration services while maintaining stable and efficient system performance. Simulation results show that our suggested solutions can efficiently evaluate the trust level of ICVs and achieve efficient and secure intelligent vehicular collaboration with acceptable communication and computation overheads.

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How to Mitigate DDoS Intelligently in SD-IoV: A Moving Target Defense Approach

Cited by 42 publications

References 42 publications

RSU-Based Online Intrusion Detection and Mitigation for VANET

RSU-Based Online Intrusion Detection and Mitigation for VANET

A Persistent Route Diversification Mechanism for Defending against Stealthy Crossfire Attack

Blockchain‐enhanced trust management for mobile edge computing‐enabled intelligent vehicular collaboration in the 6G era

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