FANCI : Feature-based Automated NXDomain Classification and Intelligence

被引:0
|
作者
Schueppen, Samuel [1 ]
Teubert, Dominik [2 ]
Herrmann, Patrick [1 ]
Meyer, Ulrike [1 ]
机构
[1] Rhein Westfal TH Aachen, Aachen, Germany
[2] Siemens CERT, Munich, Germany
关键词
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
FANCI is a novel system for detecting infections with domain generation algorithm (DGA) based malware by monitoring non-existent domain (NXD) responses in DNS traffic. It relies on machine-learning based classification of NXDs (i.e., domain names included in negative DNS responses), into DGA-related and benign NXDs. The features for classification are extracted exclusively from the individual NXD that is to be classified. We evaluate the system on malicious data generated by 59 DGAs from the DGArchive, data recorded in a large university's campus network, and data recorded on the internal network of a large company. We show that the system yields a very high classification accuracy at a low false positive rate, generalizes very well, and is able to identify previously unknown DGAs.
引用
收藏
页码:1165 / 1181
页数:17
相关论文
共 50 条
  • [41] A Feature-Based Classification of Triple Graph Grammar Variants
    Weidmann, Nils
    Oppermann, Robin
    Robrecht, Patrick
    [J]. PROCEEDINGS OF THE 12TH ACM SIGPLAN INTERNATIONAL CONFERENCE ON SOFTWARE LANGUAGE ENGINEERING (SLE '19), 2019, : 1 - 14
  • [42] Performance Evaluation of Feature-based Automatic Modulation Classification
    Ghasemzadeh, Pejman
    Banerjee, Subharthi
    Hempel, Michael
    Sharif, Hamid
    [J]. 2018 12TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND COMMUNICATION SYSTEMS (ICSPCS), 2018,
  • [43] Feature-based modulation classification using circular statistics
    Davidson, KL
    Goldschneider, JR
    Cazzanti, L
    Pitton, JW
    [J]. MILCOM 2004 - 2004 IEEE MILITARY COMMUNICATIONS CONFERENCE, VOLS 1- 3, 2004, : 765 - 771
  • [44] ARIMA Feature-Based Approach to Time Series Classification
    Jastrzebska, Agnieszka
    Homenda, Wladyslaw
    Pedrycz, Witold
    [J]. COMPUTATIONAL SCIENCE, ICCS 2022, PT II, 2022, : 192 - 199
  • [45] GABOR PHASE FEATURE-BASED HYPERSPECTRAL IMAGERY CLASSIFICATION
    Jia, Sen
    Xie, Huimin
    Deng, Lin
    Shen, Linlin
    [J]. 2017 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO (ICME), 2017, : 1291 - 1296
  • [46] Feature-Based Diversity Optimization for Problem Instance Classification
    Gao, Wanru
    Nallaperuma, Samadhi
    Neumann, Frank
    [J]. EVOLUTIONARY COMPUTATION, 2021, 29 (01) : 107 - 128
  • [47] Physicochemical feature-based classification of amino acid mutations
    Shen, Bairong
    Bai, Jinwei
    Vihinen, Mauno
    [J]. PROTEIN ENGINEERING DESIGN & SELECTION, 2008, 21 (01): : 37 - 44
  • [48] Feature-Based Diversity Optimization for Problem Instance Classification
    Gao, Wanru
    Nallaperuma, Samadhi
    Neumann, Frank
    [J]. PARALLEL PROBLEM SOLVING FROM NATURE - PPSN XIV, 2016, 9921 : 869 - 879
  • [49] Characterizing Genomics Repositories Using Feature-Based Classification
    Silva, Jorge Miguel
    Almeida, Joao Rafael
    [J]. DIGITAL PROFESSIONALISM IN HEALTH AND CARE: DEVELOPING THE WORKFORCE, BUILDING THE FUTURE, VOL. 298, 2022, : 167 - 168
  • [50] Local feature-based identification and classification for orchard insects
    Wen, Chenglu
    Guyer, Daniel E.
    Li, Wei
    [J]. BIOSYSTEMS ENGINEERING, 2009, 104 (03) : 299 - 307