Unveiling SDN Controller Identity through Timing Side Channel

Software-defined networking (SDN) has revolutionized the landscape of network management by decoupling control and data planes and becoming the backbone of many IT infrastructures including data centers, cloud computing, and enterprise networks. At the same time, however, the control plane has becom...

Full description

Saved in:
Bibliographic Details
Main Authors: Kyung, Sukwha, Baek, Jaejong, Ahn, Gail-Joon
Format: Conference Proceeding
Language:English
Subjects:
Accuracy
Artificial neural networks
Centralized control
Cloud computing
Data centers
Fingerprint recognition
Noise
Prevention and mitigation
Software defined networking
Timing
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Software-defined networking (SDN) has revolutionized the landscape of network management by decoupling control and data planes and becoming the backbone of many IT infrastructures including data centers, cloud computing, and enterprise networks. At the same time, however, the control plane has become a prime target for adversaries due to its critical role in network operations and centralized control functions. In this paper, we demonstrate how to discover the identity of different SDN controllers, which could be leveraged for more sophisticated attacks by adversaries. Our approach adopts a timing-based side channel and deep neural networks (DNN). To achieve this, we analyze real-world SDN traffic in a research computing center and accurately identify the controllers, minimizing the impact of random noise. Despite various factors that influence controller behaviors, our fingerprinting approach achieves an average accuracy of more than 90%. Lastly, the mitigation strategies are also discussed.
ISSN:2833-0072
DOI:10.1109/NoF62948.2024.10741434