BLOSTER: Blockchain-based System for Detection of Fraudulent Rules in Software-Defined Networks

Abstract

This work proposes BLOSTER, a lightweight and accurate detection system, which leverages the blockchain technology to detect any tampering attempt with the OpenFlow rules of the software-defined networks. We test BLOSTER on an experimental platform combining blockchain and software-defined networking technologies. Security analysis and performance results demonstrate that BLOSTER ensures full detection of fraudulent rules within short detection time.

Contributors

Abdelouahid Derhab

Mohamed Guerroumi

Leandros Maglaras

Mohamed Amine Ferrag

Mithun Mukherjee

Farrukh Aslam Khan

Conference

Publication date: September 2019

Publication date (Print): September 2019

Pages: 38-40

Affiliations

King Saud University

Saudi Arabia

USTHB University

Algeria

De Montfort University

UK

Guelma University

Algeria

Guangdong University of Petrochemical Technology

China

Article

DOI: 10.14236/ewic/icscsr19.5

Copyright statement: © Abdelouahid Derhab et al. Published by BCS Learning and Development Ltd. 6th International Symposium for ICS & SCADA Cyber Security Research 2019

License:

This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

Conference name: 6th International Symposium for ICS & SCADA Cyber Security Research 2019

Conference acronym: ICS-CSR

Conference number: 6

Conference location: Athens, Greece

Conference date: 10th-12th September 2019

Conference sponsor: Electronic Workshops in Computing (eWiC)

Conference theme: Cyber Security Research

Product

Product Information: 1477-9358BCS Learning & Development

Self URI (article page): https://www.scienceopen.com/hosted-document?doi=10.14236/ewic/icscsr19.5

Self URI (journal page): https://ewic.bcs.org/

Categories

Series title: Electronic Workshops in Computing