Next Article in Journal
Using Noise Level to Detect Frame Repetition Forgery in Video Frame Rate Up-Conversion
Previous Article in Journal
On the Security of Rotation Operation Based Ultra-Lightweight Authentication Protocols for RFID Systems
Article Menu
Issue 9 (September) cover image

Export Article

Open AccessArticle
Future Internet 2018, 10(9), 83; https://doi.org/10.3390/fi10090083

A HMM-R Approach to Detect L-DDoS Attack Adaptively on SDN Controller

College of Computer Science, South-Central University for Nationalities, Wuhan 430074, China
*
Author to whom correspondence should be addressed.
Received: 27 July 2018 / Revised: 16 August 2018 / Accepted: 21 August 2018 / Published: 23 August 2018
(This article belongs to the Section Smart System infrastructures and Cybersecurity)
Full-Text   |   PDF [2251 KB, uploaded 23 August 2018]   |  

Abstract

A data center network is vulnerable to suffer from concealed low-rate distributed denial of service (L-DDoS) attacks because its data flow has the characteristics of data flow delay, diversity, and synchronization. Several studies have proposed addressing the detection of L-DDoS attacks, most of them are only detect L-DDoS attacks at a fixed rate. These methods cause low true positive and high false positive in detecting multi-rate L-DDoS attacks. Software defined network (SDN) is a new network architecture that can centrally control the network. We use an SDN controller to collect and analyze data packets entering the data center network and calculate the Renyi entropies base on IP of data packets, and then combine them with the hidden Markov model to get a probability model HMM-R to detect L-DDoS attacks at different rates. Compared with the four common attack detection algorithms (KNN, SVM, SOM, BP), HMM-R is superior to them in terms of the true positive rate, the false positive rate, and the adaptivity. View Full-Text
Keywords: L-DDoS attacks; SDN; data center network; adaptive detection; HMM-R L-DDoS attacks; SDN; data center network; adaptive detection; HMM-R
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Wang, W.; Ke, X.; Wang, L. A HMM-R Approach to Detect L-DDoS Attack Adaptively on SDN Controller. Future Internet 2018, 10, 83.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Future Internet EISSN 1999-5903 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top