Protecting Software-Defined Enterprise Networks from Packet Injection Attacks

Abstract

Packet injection attacks are a primary threat to software-defined enterprise networks, for which continuous connectivity and real-time network functioning are two essential requirements. They are a form of denial-of-service attacks, and their main effect is network performance degradation up to total breakdown. In this paper, we show how such an attack can effectively be detected and mitigated at the entrance gateway switch of the software-defined enterprise network without sacrificing the basic functionality and performance of the networks control mechanisms. We describe an effective protection of the network's core controller as well as a significant reduction of rule-space overhead compared to a state-of-the-art technique.

Defending Sdn Against Packet Injection Attacks Using Deep Learning

“…Our interest in this study is focused on designing a deterministic technique to detect and mitigate packetinjection attacks. More recently, ul Huque and Hartog [22] presented a workload offloading approach to protect SDN from packet-injection attacks. According to this approach, when malicious traffic inflow crosses a certain threshold, the edge controller controls the core controller.…”

“…Thus, the core controller remains available even when the gateway switch is attacked. Unlike [22], our work uses deep learning to detect and mitigate attacks.…”