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  1. Proceedings of the 2015 Workshop on Automated Decision Making for Active Cyber Defense (SafeConfig '15)
  2. FlowMon: Detecting Malicious Switches in Software-Defined Networks
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Integrated Adaptive Cyber Defense: Integration Spiral Results
Action Recommendation for Cyber Resilience
Using Probability Densities to Evolve more Secure Software Configurations
Automated Decision Making for Active Cyber Defense: Panel Discussion
Cyber Resilience-by-Construction: Modeling, Measuring & Verifying
Policy Specialization to Support Domain Isolation
Estimating Risk Boundaries for Persistent and Stealthy Cyber-Attacks
FlowMon: Detecting Malicious Switches in Software-Defined Networks
Who Touched My Mission: Towards Probabilistic Mission Impact Assessment
A Security Enforcement Framework for Virtual Machine Migration Auction
Behavior-dependent Routing: Responding to Anomalies with Automated Low-cost Measures

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FlowMon: Detecting Malicious Switches in Software-Defined Networks

Content Provider ACM Digital Library
Author KamisiƄski, Andrzej Fung, Carol
Abstract Software-Defined Networking (SDN) introduces a new communication network management paradigm and has gained much attention recently. In SDN, a network controller overlooks and manages the entire network by configuring routing mechanisms for underlying switches. The switches report their status to the controller periodically, such as port statistics and flow statistics, according to their communication protocol. However, switches may contain vulnerabilities that can be exploited by attackers. A compromised switch may not only lose its normal functionality, but it may also maliciously paralyze the network by creating network congestions or packet loss. Therefore, it is important for the system to be able to detect and isolate malicious switches. In this work, we investigate a methodology for an SDN controller to detect compromised switches through real-time analysis of the periodically collected reports. Two types of malicious behavior of compromised switches are investigated: packet dropping and packet swapping. We proposed two anomaly detection algorithms to detect packet droppers and packet swappers. Our simulation results show that our proposed methods can effectively detect packet droppers and swappers. To the best of our knowledge, our work is the first to address malicious switches detection using statistics reports in SDN.
Starting Page 39
Ending Page 45
Page Count 7
File Format PDF
ISBN 9781450338219
DOI 10.1145/2809826.2809833
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2015-10-12
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Software-defined networking Malicious behavior Openflow Network security Sdn Anomaly detection
Content Type Text
Resource Type Article
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