Malicious DNS Tunneling Detection in Real-Traffic DNS Data

被引:11
|
作者
Lambion, Danielle [1 ]
Josten, Michael [1 ]
Olumofin, Femi [2 ]
De Cock, Martine [1 ]
机构
[1] Univ Washington, Sch Engn & Technol, Tacoma, WA 98402 USA
[2] Infoblox, Santa Clara, CA USA
关键词
DNS tunneling; random forest; CNN;
D O I
10.1109/BigData50022.2020.9378418
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
While originally not intended for data transfer, the Domain Name System (DNS) is currently used to this end anyway, in a process called DNS tunneling (DNST). Malicious users exploit DNST for data exfiltration from infected machines, posing a critical security threat. We train and evaluate state-of-the-art convolutional neural network, random forest, and ensemble classifiers to detect tunneling in DNS traffic. Finally, we assess the classifiers' performance and robustness by exposing them to one day of real-traffic data.
引用
收藏
页码:5736 / 5738
页数:3
相关论文
共 50 条
  • [41] A DNS Tunneling Detection Method Based on Deep Learning Models to Prevent Data Exfiltration
    Zhang, Jiacheng
    Yang, Li
    Yu, Shui
    Ma, Jianfeng
    NETWORK AND SYSTEM SECURITY, NSS 2019, 2019, 11928 : 520 - 535
  • [42] Real-time Malicious Fast-flux Detection Using DNS and Bot Related Features
    Martinez-Bea, Sergi
    Castillo-Perez, Sergio
    Garcia-Alfaro, Joaquin
    2013 ELEVENTH ANNUAL INTERNATIONAL CONFERENCE ON PRIVACY, SECURITY AND TRUST (PST), 2013, : 369 - 372
  • [43] A Deep Learning Based Online Malicious URL and DNS Detection Scheme
    Jiang, Jianguo
    Chen, Jiuming
    Choo, Kim-Kwang Raymond
    Liu, Chao
    Liu, Kunying
    Yu, Min
    Wang, Yongjian
    SECURITY AND PRIVACY IN COMMUNICATION NETWORKS, SECURECOMM 2017, 2018, 238 : 438 - 448
  • [44] Botnet detection by monitoring group activities in DNS traffic
    Choi, Hyunsang
    Lee, Hanwoo
    Lee, Heejo
    Kim, Hyogon
    2007 CIT: 7TH IEEE INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION TECHNOLOGY, PROCEEDINGS, 2007, : 715 - 720
  • [45] MalPortrait: Sketch Malicious Domain Portraits Based on Passive DNS Data
    Liang, Zhizhou
    Zang, Tianning
    Zeng, Yuwei
    2020 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC), 2020,
  • [46] Fast-flucos: malicious domain name detection method for Fast-flux based on DNS traffic
    Han C.
    Zhang Y.
    Zhang Y.
    Tongxin Xuebao/Journal on Communications, 2020, 41 (05): : 37 - 47
  • [47] BotCVD: Visual analysis of DNS traffic for botnet detection
    Jiang, H. (hellojhl@163.com), 1600, Advanced Institute of Convergence Information Technology (04):
  • [48] Discovering Malicious Domains through Passive DNS Data Graph Analysis
    Khalil, Issa
    Yu, Ting
    Guan, Bei
    ASIA CCS'16: PROCEEDINGS OF THE 11TH ACM ASIA CONFERENCE ON COMPUTER AND COMMUNICATIONS SECURITY, 2016, : 663 - 674
  • [49] A New Statistical Approach to DNS Traffic Anomaly Detection
    Yuchi, Xuebiao
    Wang, Xin
    Lee, Xiaodong
    Yan, Baoping
    ADVANCED DATA MINING AND APPLICATIONS (ADMA 2010), PT II, 2010, 6441 : 302 - 313
  • [50] Supervised Learning Approaches with Majority Voting for DNS Tunneling Detection
    Aiello, Maurizio
    Mongelli, Maurizio
    Papaleo, Gianluca
    INTERNATIONAL JOINT CONFERENCE SOCO'14-CISIS'14-ICEUTE'14, 2014, 299 : 463 - 472