POAGuard: A Defense Mechanism Against Preemptive Table Overflow Attack in Software-Defined Networks

被引:0
|
作者
Liu, Yuming [1 ]
Wang, Yong [1 ]
Feng, Hao [1 ]
机构
[1] Guilin Univ Elect Technol, Sch Comp & Informat Secur, Guilin 541004, Peoples R China
基金
中国国家自然科学基金;
关键词
SDN; flow table overflow; preemptive overflow attack; attack detection;
D O I
10.1109/ACCESS.2023.3330224
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In Software-Defined Networks (SDN), the limited flow table capacity of switches makes them susceptible to flow table overflow attacks, which can lead to performance degradation or network corruption. Prior research has mainly focused on rate-based overflow attacks (ROA), which exhibit varying attack effects depending on the overflow rate. This study introduces a novel attack called the preemptive overflow attack (POA), which exploits flow entry eviction mechanism to preempt the flow entries of normal applications, resulting in amplified performance degradation. Notably, when using the widely deployed Least Frequently Used (LFU) eviction algorithm, POA achieves a significant impact while consuming fewer flow entries than existing ROA methods. Furthermore, the detection of POA remains challenging owing to the lack of distinctive flow features. To mitigate POA, we propose POAGuard as a defense mechanism. POAGuard incorporates a table segmentation method for table management, a score-based eviction algorithm that evicts suspicious flow entries, and a concept drift-based detection method that identifies and defends against POA. Extensive experiments are conducted to verify the effectiveness of POAGuard, and the results demonstrate that POAGuard can effectively defend against POA.
引用
收藏
页码:123659 / 123676
页数:18
相关论文
共 50 条
  • [21] Analysis and a Defense Method for Overflow Vulnerability of Flow Tables in Software Defined Networks
    Zhou Y.
    Chen K.
    Leng J.
    Hu C.
    Hsi-An Chiao Tung Ta Hsueh/Journal of Xi'an Jiaotong University, 2017, 51 (10): : 53 - 58
  • [22] Heterogeneous Flow Table Integration for Capacity Enhancement in Software-Defined Networks
    Hung, Chi-Hsiang
    Wang, Jheng-Jyun
    Wang, Li-Chun
    Wang, Kuo-Chen
    Lee, Chain-Wu
    2018 INTERNATIONAL CONFERENCE ON COMPUTING, NETWORKING AND COMMUNICATIONS (ICNC), 2018, : 832 - 836
  • [23] Proactive multipath routing with a predictive mechanism in software-defined networks
    Lin, Ying-Dar
    Liu, Te-Lung
    Wang, Shun-Hsien
    Lai, Yuan-Cheng
    INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, 2019, 32 (14)
  • [24] Future Scenarios for Software-Defined Metro and Access Networks and Software-Defined Photonics
    Muciaccia, Tommaso
    Passaro, Vittorio M. N.
    PHOTONICS, 2017, 4 (01)
  • [25] Detecting DDoS based on attention mechanism for Software-Defined Networks
    Yoon, Namkyung
    Kim, Hwangnam
    JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2024, 230
  • [26] Intrusion Prevention with Attack Traceback and Software-defined Control Plane for Campus Networks
    Guo, Guangfeng
    Zhang, Junxing
    Ma, Zhanfei
    COMPUTER SCIENCE AND INFORMATION SYSTEMS, 2021, 18 (03) : 867 - 891
  • [27] Securing Software-Defined Networks Through Adaptive Moving Target Defense Capabilities
    Silva, Felipe Dantas S.
    Neto, Emidio P.
    Nunes, Rodrigo S. S.
    Souza, Cristian H. M.
    Neto, Augusto J. V.
    Pascoal, Tulio
    JOURNAL OF NETWORK AND SYSTEMS MANAGEMENT, 2023, 31 (03)
  • [28] Citadel: Cyber threat intelligence assisted defense system for software-defined networks
    Yurekten, Ozgur
    Demirci, Mehmet
    COMPUTER NETWORKS, 2021, 191
  • [29] Fast Defense System Against Attacks in Software Defined Networks
    De Assis, Marcos V. O.
    Novaes, Matheus P.
    Zerbini, Cinara B.
    Carvalho, Luiz F.
    Abrao, Taufik
    Proenca, Mario L., Jr.
    IEEE ACCESS, 2018, 6 : 69620 - 69639
  • [30] DDoS Attack Detection Method Based on Improved KNN With the Degree of DDoS Attack in Software-Defined Networks
    Dong, Shi
    Sarem, Mudar
    IEEE ACCESS, 2020, 8 : 5039 - 5048