An Efficient SDN-Based DDoS Attack Detection and Rapid Response Platform in Vehicular Networks

Yao, Yu; Guo, Lei; Liu, Ye; Zheng, Jian; Zong, Yue

doi:10.1109/access.2018.2854567

Cited by 89 publications

(53 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, Floodlight also introduces an OpenFlow audit subsystem to track all security relevant-events that occur between the control data plane and the application layer. Based on Floodlight Framework, Yu et al [15] design a platform to efficiently detect and rapidly respond to the DDoS attacks in vehicular networks. Simulation results show that the proposed system significantly shortens the response time to the attack and reduces the burden on the controller.…”

Section: ) Sdn and Nfv Technologiesmentioning

confidence: 99%

A Survey on the Current Security Landscape of Intelligent Transportation Systems

Lamssaggad¹,

Benamar²,

Hafid³

et al. 2021

IEEE Access

112

View full text Add to dashboard Cite

With the proliferation of embedded technologies and wireless capabilities, today's vehicles are no longer isolated mechanical machines. They become part of a hyper-connected system-Intelligent Transportation Systems (ITS)-that has the potential to support multiple levels of autonomy and intelligence improving considerably the safety, efficiency, and sustainability of transportation networks. However, this raises new security issues that make the whole system prone to cybersecurity attacks that threaten both the safety and privacy of all road-users. This paper gives a short background tutorial on the main security issues and the different attacks that hinder Intelligent Transport Systems. To enable secure and safe ITS applications, this paper provides a comprehensive analysis of existing solutions and highlights their strengths and limitations. Finally, this survey presents key challenges in the field, and discusses recent trends that must be factored in by researchers, implementers, and car manufactures to improve the security of ITS.

show abstract

Section: ) Sdn and Nfv Technologiesmentioning

confidence: 99%

A Survey on the Current Security Landscape of Intelligent Transportation Systems

Lamssaggad¹,

Benamar²,

Hafid³

et al. 2021

IEEE Access

112

View full text Add to dashboard Cite

show abstract

“…In the literature, few IDS models have been proposed by researchers to detect ICMPv4-based DDoS attacks using ML techniques for SDN-based architectures, such as [75], [76], [77], and [78]. However, the common technique used by administrators as a solution for ICMPv4-based DDoS attacks was the rate limitation or complete blocking of ICMPv4 messages in an IPv4 network [31].…”

Section: A Leveraging New Network Architecturementioning

confidence: 99%

ICMPv6-Based DoS and DDoS Attacks Detection Using Machine Learning Techniques, Open Challenges, and Blockchain Applicability: A Review

2020

View full text Add to dashboard Cite

Although the launch of Internet Protocol version six (IPv6) addressed the issue of IPv4's address depletion, but also mandated the use of Internet Control Message Protocol version six (ICMPv6) messages in newly introduced features such as the Neighbor Discovery Protocol (NDP). This has exacerbated existing network attacks including ICMPv6-based Denial of Service (DoS) attacks and its variant form Distributed Denial of Service (DDoS) attack. Intrusion Detection Systems (IDS) aimed at tackling security issues raised by ICMPv6-based DoS and DDoS attacks have been reviewed by researchers and a general classification of existing IDSs was proposed as anomaly-based and signature-based. However, it is incredibly hard to see the overall picture of IDSs based on Machine Learning (ML) techniques with such a classification, as there is a lack of a more detailed view of the ML approach, classifiers, feature selection techniques, datasets, and different evaluation metrics. Nevertheless, recent developments in this relatively new field have not been covered such as ML-based IDSs using flow-based traffic representation. Therefore, this paper specifically reviews and classifies IDSs based on ML techniques to detect ICMPv6-based DoS and DDoS attacks as single and hybrid classifiers. In addition, blockchain applicability in Collaborative IDS (CIDS) architecture based on the ensemble framework has been proposed as a solution to one of the open challenges for ICMPv6-based DoS and DDoS attacks detection problem. Moreover, this review also provides a classification of ICMPv6 vulnerabilities to DoS and DDoS attacks which would provide a reference resource for future researchers in this domain. To the best of the author's knowledge, this is the first review paper specifically focusing on IDSs based on ML techniques in this domain, as well as blockchain applicability as a possible research direction has been proposed to attract researcher's focus on building ensemble learning-based IDS models.

show abstract

“…Support vector machine can be used as an efficient DDoS detection technique in Vehicular networks platform [17]. The authors have proposed the platform that contains the trigger mechanism of OpenFlow protocols for a response and involves the flow feature extraction strategies based on the different dimensional information.…”

Section: Related Workmentioning

confidence: 99%

Analysis of Features Dataset for DDoS Detection by using ASVM Method on Software Defined Networking

Oo¹,

Kamolphiwong²,

Kamolphiwong³

et al. 2020

IJNDC

View full text Add to dashboard Cite

With the continuous development of networking environment, nowadays, there are many innovative technologies in computer network researches and industries. Most businesses use various mobile devices, cloud services and virtualization techniques in network environments [1]. Their usage is becoming the strongest evolution. The network programmability will be critical for business growth. Most of the today's network types are traditional networks. The traditional network management methods are device-bydevice and system by using manual configurations [2]. All devices are controlled and managed by human. If a new network device is added to the network, the device must be first configured. As a result, the network is not flexible and cannot be easily scale.

show abstract

An Efficient SDN-Based DDoS Attack Detection and Rapid Response Platform in Vehicular Networks

Cited by 89 publications

References 26 publications

A Survey on the Current Security Landscape of Intelligent Transportation Systems

A Survey on the Current Security Landscape of Intelligent Transportation Systems

ICMPv6-Based DoS and DDoS Attacks Detection Using Machine Learning Techniques, Open Challenges, and Blockchain Applicability: A Review

Analysis of Features Dataset for DDoS Detection by using ASVM Method on Software Defined Networking

Contact Info

Product

Resources

About