Greedy Algorithms for Network Anomaly Detection

被引：0
|
作者：
Andrysiak, Tomasz [1 ]
Saganowski, Lukasz [1 ]
Choras, Michal [1 ]
机构：
[1] Univ Technol & Life Sci Bydgoszcz, Inst Telecommun, PL-85789 Bydgoszcz, Poland
来源：
INTERNATIONAL JOINT CONFERENCE CISIS'12 - ICEUTE'12 - SOCO'12 SPECIAL SESSIONS | 2013年 / 189卷
关键词：
network anomaly detection; cybersecurity; greedy algorithms;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper we focus on increasing cybersecurity by means of greedy algorithms applied to network anomaly detection task. In particular, we propose to use Matching Pursuit and Orthogonal Matching Pursuit algorithms. The major contribution of the paper is the proposition of 1D KSVD structured dictionary for greedy algorithm as well as its tree based structure representation (clusters). The promising results for 15 network metrics are reported and compared to DWT-based approach.
引用
收藏
页码：235 / 244
页数：10
相关论文
共 50 条
  • [1] Network Anomaly Detection Using Header Information With Greedy Algorithm
    Ates, Cagatay
    Ozdel, Suleyman
    Yildirim, Metehan
    Anarim, Emin
    [J]. 2019 27TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU), 2019,
  • [2] On the Use of Compression Algorithms for Network Anomaly Detection
    Callegari, Christian
    Giordano, Stefano
    Pagano, Michele
    [J]. 2009 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS, VOLS 1-8, 2009, : 636 - 640
  • [3] Greedy Ensemble Hyperspectral Anomaly Detection
    Hossain, Mazharul
    Younis, Mohammed
    Robinson, Aaron
    Wang, Lan
    Preza, Chrysanthe
    [J]. JOURNAL OF IMAGING, 2024, 10 (06)
  • [4] Network Intrusion Detection Using Machine Learning Anomaly Detection Algorithms
    Hanifi, Khadija
    Bank, Hasan
    Karsligil, M. Elif
    Yavuz, A. Gokhan
    Guvensan, M. Amac
    [J]. 2017 25TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU), 2017,
  • [5] Machine Learning-Driven Algorithms for Network Anomaly Detection
    Islam, Md Sirajul
    Rouf, Mohammad Abdur
    Parvez, A. H. M. Shahariar
    Podder, Prajoy
    [J]. INVENTIVE COMPUTATION AND INFORMATION TECHNOLOGIES, ICICIT 2021, 2022, 336 : 493 - 507
  • [6] Study and Evaluation of Unsupervised Algorithms Used in Network Anomaly Detection
    Dromard, Juliette
    Owezarski, Philippe
    [J]. PROCEEDINGS OF THE FUTURE TECHNOLOGIES CONFERENCE (FTC) 2019, VOL 2, 2020, 1070 : 397 - 416
  • [7] Anomaly detection via adaptive greedy model
    Hou, Dongdong
    Cong, Yang
    Sun, Gan
    Liu, Ji
    Xu, Xiaowei
    [J]. NEUROCOMPUTING, 2019, 330 : 369 - 379
  • [8] A New Network Anomaly Detection Method Based on Header Information Using Greedy Algorithm
    Ates, Cagalay
    Ozdel, Suleyman
    Anarim, Eniin
    [J]. 2019 6TH INTERNATIONAL CONFERENCE ON CONTROL, DECISION AND INFORMATION TECHNOLOGIES (CODIT 2019), 2019, : 657 - 662
  • [9] Corporate network anomaly detection methodology utilizing machine learning algorithms
    Baisholan, Nazerke
    Baisholanova, Karlygash
    Kubayev, Kazila
    Alimzhanova, Zhanna
    Baimuldina, Nazira
    [J]. SMART SCIENCE, 2024,
  • [10] Studies in Applying PCA and Wavelet Algorithms for Network Traffic Anomaly Detection
    Novakov, Stevan
    Lung, Chung-Horng
    Lambadaris, Ioannis
    Seddigh, Nabil
    [J]. 2013 IEEE 14TH INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE SWITCHING AND ROUTING (HPSR), 2013, : 185 - 190
12345