Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Counteracting UDP flooding attacks in SDN

Tung, Yung-Hao, Wei, Hung-Chuan, Ti, Yen-Wu, Tsou, Yao-Tung, Saxena, Neetesh and Yu, Chia-Mu 2020. Counteracting UDP flooding attacks in SDN. Electronics 9 (8) , 1239. 10.3390/electronics9081239

[img]
Preview
PDF - Published Version
Available under License Creative Commons Attribution.

Download (2MB) | Preview

Abstract

Software-defined networking (SDN) is a new networking architecture with a centralized control mechanism. SDN has proven to be successful in improving not only the network performance, but also security. However, centralized control in the SDN architecture is associated with new security vulnerabilities. In particular, user-datagram-protocol (UDP) flooding attacks can be easily launched and cause serious packet-transmission delays, controller-performance loss, and even network shutdown. In response to applications in the Internet of Things (IoT) field, this study considers UDP flooding attacks in SDN and proposes two lightweight countermeasures. The first method sometimes sacrifices address-resolution-protocol (ARP) requests to achieve a high level of security. In the second method, although packets must sometimes be sacrificed when undergoing an attack before starting to defend, the detection of the network state can prevent normal packets from being sacrificed. When blocking a network attack, attacks from the affected port are directly blocked without affecting normal ports. The performance and security of the proposed methods were confirmed by means of extensive experiments. Compared with the situation where no defense is implemented, or similar defense methods are implemented, after simulating a UDP flooding attack, our proposed method performed better in terms of the available bandwidth, centralprocessing-unit (CPU) consumption, and network delay time.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Publisher: MDPI
ISSN: 2079-9292
Date of First Compliant Deposit: 3 August 2020
Date of Acceptance: 31 July 2020
Last Modified: 10 Sep 2020 12:48
URI: http://orca.cf.ac.uk/id/eprint/133898

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics