Investigating Vulnerabilities in OpenFlow Discovery Protocol: Novel Attacks and Their Defense

Software-defined networking (SDN) enables network visibility and intelligence by providing a global topology view. The controller maintains and updates the real-time topology using the OpenFlow Discovery Protocol (OFDP). However, without robust security mechanisms, OFDP introduces new security threats to the network. This paper investigates the security threats of OFDP packets, focusing specifically on their header fields and data units. We propose novel methods to implement existing attacks and bypass current defenses. In addition, we identify two new vulnerabilities that allow for the manipulation of link information and the exhaustion of network resources. Through a series of experiments, we demonstrate the feasibility of these attacks. Our findings have been responsibly disclosed to Floodlight, and two CVEs ( CVE-2024-57672 and CVE-2024-57673) were assigned. To defend against such attacks, we design <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LOFDP</i> to enhance the security of OFDP by thoroughly inspecting the header fields and encrypting the data units. As a lightweight extension of existing controllers, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LOFDP</i> can filter malformed packets to prevent attacks, balancing scalability and security. We implement a prototype of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LOFDP</i> and evaluate its effectiveness and performance in a simulated environment. The results show that <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LOFDP</i> can effectively prevent attacks with negligible latency.

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Publication Details

Journal
IEEE Transactions on Dependable and Secure Computing
Published
2025-06-30
DOI
https://doi.org/10.1109/tdsc.2025.3584851
Citations
1
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
1.49
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article

Investigating Vulnerabilities in OpenFlow Discovery Protocol: Novel Attacks and Their Defense

Shuhua Deng, Xieping Gao, Zijuan Yin
1 citations
IEEE Transactions on Dependable and Secure Computing
Advanced Malware Detection Techniques
1.49
article

Investigating Vulnerabilities in OpenFlow Discovery Protocol: Novel Attacks and Their Defense

Shuhua Deng, Xieping Gao, Zijuan Yin
article en
1 citations

Abstract

Software-defined networking (SDN) enables network visibility and intelligence by providing a global topology view. The controller maintains and updates the real-time topology using the OpenFlow Discovery Protocol (OFDP). However, without robust security mechanisms, OFDP introduces new security threats to the network. This paper investigates the security threats of OFDP packets, focusing specifically on their header fields and data units. We propose novel methods to implement existing attacks and bypass current defenses. In addition, we identify two new vulnerabilities that allow for the manipulation of link information and the exhaustion of network resources. Through a series of experiments, we demonstrate the feasibility of these attacks. Our findings have been responsibly disclosed to Floodlight, and two CVEs ( CVE-2024-57672 and CVE-2024-57673) were assigned. To defend against such attacks, we design <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LOFDP</i> to enhance the security of OFDP by thoroughly inspecting the header fields and encrypting the data units. As a lightweight extension of existing controllers, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LOFDP</i> can filter malformed packets to prevent attacks, balancing scalability and security. We implement a prototype of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LOFDP</i> and evaluate its effectiveness and performance in a simulated environment. The results show that <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LOFDP</i> can effectively prevent attacks with negligible latency.

IEEE Transactions on Dependable and Secure ComputingVol. 22(6)
Hunan Normal University (CN), Xiangtan University (CN)
Openalex Percentile: Top 17%
Advanced Malware Detection Techniques
1.49
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