Ransomware detection and mitigation using software-defined networking: The case of WannaCry

被引:52
|
作者
Akbanov, Maxat [1 ]
Vassilakis, Vassilios G. [1 ]
Logothetis, Michael D. [2 ]
机构
[1] Univ York, Dept Comp Sci, York, N Yorkshire, England
[2] Univ Patras, Dept Elect & Comp Engn, Patras, Greece
关键词
WannaCry; Ransomware; Software-defined networking; OpenFlow; Malware analysis;
D O I
10.1016/j.compeleceng.2019.03.012
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Modern day ransomware families implement sophisticated encryption and propagation schemes, thus limiting chances to recover the data almost to zero. We investigate the use of software-defined networking (SDN) to detect and mitigate advanced ransomware threat. We present our ransomware analysis results and our developed SDN-based security framework. For the proof of concept, the infamous WannaCry ransomware was used. Based on the obtained results, we design an SDN detection and mitigation framework and develop a solution based on OpenFlow. The developed solution detects suspicious activities through network traffic monitoring and blocks infected hosts by adding flow table entries into OpenFlow switches in a real-time manner. Finally, our experiments with multiple samples of WannaCry show that the developed mechanism in all cases is able to promptly detect the infected machines and prevent WannaCry from spreading. (C) 2019 Elsevier Ltd. All rights reserved.
引用
收藏
页码:111 / 121
页数:11
相关论文
共 50 条
  • [1] Using Software-Defined Networking for Ransomware Mitigation: The Case of CryptoWall
    Cabaj, Krzysztof
    Mazurczyk, Wojciech
    IEEE NETWORK, 2016, 30 (06): : 14 - 20
  • [2] An ecosystem for anomaly detection and mitigation in software-defined networking
    Carvalho, Luiz Fernando
    Abrao, Taufik
    Mendes, Leonardo de Souza
    Proenca, Mario Lemes, Jr.
    EXPERT SYSTEMS WITH APPLICATIONS, 2018, 104 : 121 - 133
  • [3] Phishlimiter: A Phishing Detection and Mitigation Approach Using Software-Defined Networking
    Chin, Tommy, Jr.
    Xiong, Kaiqi
    Hu, Chengbin
    IEEE ACCESS, 2018, 6 : 42516 - 42531
  • [4] Software-defined networking-based crypto ransomware detection using HTTP traffic characteristics
    Cabaj, Krzysztof
    Gregorczyk, Marcin
    Mazurczyk, Wojciech
    COMPUTERS & ELECTRICAL ENGINEERING, 2018, 66 : 353 - 368
  • [5] Detection and Mitigation of DDoS Attacks Using Conditional Entropy in Software-defined Networking
    Xuanyuan, Ming
    Ramsurrun, Visham
    Seeam, Amar
    2019 11TH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTING (ICOAC 2019), 2019, : 66 - 71
  • [6] Improved Network Monitoring Using Software-Defined Networking for DDoS Detection and Mitigation Evaluation
    J. Ramprasath
    V. Seethalakshmi
    Wireless Personal Communications, 2021, 116 : 2743 - 2757
  • [7] Improved Network Monitoring Using Software-Defined Networking for DDoS Detection and Mitigation Evaluation
    Ramprasath, J.
    Seethalakshmi, V.
    WIRELESS PERSONAL COMMUNICATIONS, 2021, 116 (03) : 2743 - 2757
  • [8] FADM: DDoS Flooding Attack Detection and Mitigation System in Software-Defined Networking
    Hu, Dingwen
    Hong, Peilin
    Chen, Yixin
    GLOBECOM 2017 - 2017 IEEE GLOBAL COMMUNICATIONS CONFERENCE, 2017,
  • [9] A Software-defined Networking-based Detection and Mitigation Approach against KRACK
    Li, Yi
    Serrano, Marcos
    Chin, Tommy
    Xiong, Kaiqi
    Lin, Jing
    PROCEEDINGS OF THE 16TH INTERNATIONAL JOINT CONFERENCE ON E-BUSINESS AND TELECOMMUNICATIONS, VOL 2: SECRYPT, 2019, : 244 - 251
  • [10] Malware Detection for Mobile Devices Using Software-Defined Networking
    Jin, Ruofan
    Wang, Bing
    2013 SECOND GENI RESEARCH AND EDUCATIONAL EXPERIMENT WORKSHOP (GREE), 2013, : 81 - 88