The HoneyTank: A scalable approach to collect malicious internet traffic

被引:4
|
作者
Vanderavero, Nicolas [1 ]
Brouckaert, Xavier [1 ]
Bonaventure, Olivier [1 ]
Le Charlier, Baudouin [1 ,2 ]
机构
[1] Department of Computing Science and Engineering, Universiteá Catholique de Louvain (UCL), Belgium
[2] Computing Science Department, Catholic University of Louvain-la-Neuve
关键词
Computational methods - Computer worms - Internet protocols - Intrusion detection;
D O I
10.1504/IJCIS.2008.016100
中图分类号
学科分类号
摘要
In this paper, we propose an efficient method for collecting large amounts of malicious internet traffic. The key advantage of our method is that it does not need to maintain any state to emulate TCP services running on a large number of emulated end-systems. We implemented a prototype on the ASAX intrusion detection system and we provide several examples of the malicious activities that were collected on a campus network attached to the internet. We explain how we implemented various protocols in a stateless way. We also discuss how our method can be improved to make an accurate but still stateless emulation of stateful protocols. Copyright © 2008 Inderscience Enterprises Ltd.
引用
收藏
页码:185 / 205
相关论文
共 50 条
  • [1] Toward an efficient and scalable feature selection approach for internet traffic classification
    Fahad, Adil
    Tari, Zahir
    Khalil, Ibrahim
    Habib, Ibrahim
    Alnuweiri, Hussein
    COMPUTER NETWORKS, 2013, 57 (09) : 2040 - 2057
  • [2] Malicious Web traffic detection for Internet of Things environments
    Yong, Binbin
    Liu, Xin
    Yu, Qingchen
    Huang, Liang
    Zhou, Qingguo
    COMPUTERS & ELECTRICAL ENGINEERING, 2019, 77 : 260 - 272
  • [3] Internet traffic classification for scalable QoS provision
    Park, Junghun
    Tyan, Hsiao-Rong
    Kuo, C. -C. Jay
    2006 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO - ICME 2006, VOLS 1-5, PROCEEDINGS, 2006, : 1221 - 1224
  • [4] Malicious Traffic Compression and Classification Technique for Secure Internet of Things
    Lee, Yu-Rim
    Park, Na-Eun
    Kim, Seo-Yi
    Lee, Il-Gu
    CMC-COMPUTERS MATERIALS & CONTINUA, 2023, 76 (03): : 3465 - 3482
  • [5] Transformer-Based Malicious Traffic Detection for Internet of Things
    Luo, Yantian
    Chen, Xu
    Ge, Ning
    Feng, Wei
    Lu, Jianhua
    IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC 2022), 2022, : 4187 - 4192
  • [6] LightGuard: A Lightweight Malicious Traffic Detection Method for Internet of Things
    Huo, Yuehua
    Liang, Wei
    Chen, Junhan
    Zhuang, Shangyuan
    Sun, Jiyan
    IEEE INTERNET OF THINGS JOURNAL, 2024, 11 (17): : 28566 - 28577
  • [7] SDC: A scalable approach to collect data in wireless sensor networks
    Thepvilojanapong, N
    Tobe, Y
    Sezaki, K
    IEICE TRANSACTIONS ON COMMUNICATIONS, 2005, E88B (03) : 890 - 902
  • [8] A scalable solution for engineering streaming traffic in the future Internet
    Baldi, Mario
    Marchetto, Guido
    Ofek, Yoram
    COMPUTER NETWORKS, 2007, 51 (14) : 4092 - 4111
  • [9] Toward Scalable Internet Traffic Measurement and Analysis with Hadoop
    Lee, Yeonhee
    Lee, Youngseok
    ACM SIGCOMM COMPUTER COMMUNICATION REVIEW, 2013, 43 (01) : 6 - 13
  • [10] UAC: A Lightweight and Scalable Approach to Detect Malicious Web Pages
    Kaur, Harneet
    Madan, Sanjay
    Sehgal, Rakesh Kumar
    MODERN TRENDS AND TECHNIQUES IN COMPUTER SCIENCE (CSOC 2014), 2014, 285 : 241 - 261