A new approach to intrusion detection in databases by using artificial neuro fuzzy inference system

被引:0
|
作者
Department of Computer Science and Engineering and IT, Veer Surendra Sai University of Technology, Burla, Odisha, India [1 ]
机构
[1] Department of Computer Science and Engineering and IT, Veer Surendra Sai University of Technology, Burla, Odisha
来源
Int. J. Reasoning based Intell. Syst. | / 3-4卷 / 254-260期
关键词
ANFIS; ANN; Artificial neural network; Artificial neuro fuzzy inference system; Database security; FIS; Fuzzy inference system; Intrusion detection;
D O I
10.1504/IJRIS.2015.072952
中图分类号
学科分类号
摘要
In this modern era of internet, security of data has become a primary concern due to exposure of databases on the web. The present study approaches the problem of database intrusion detection from a pattern recognition point of view, where artificial neuro fuzzy inference system (ANFIS) is used to capture user behavioural patterns. In this paper, we have proposed a database intrusion detection system using ANFIS as a classifier that is capable of outperforming in many ways and better suits the demands and dynamic nature of the problem. The proposed approach to intrusion detection gives a better detection rate and lowers the false positive rate compared to other traditional techniques. © 2015 Inderscience Enterprises Ltd.
引用
收藏
页码:254 / 260
页数:6
相关论文
共 50 条
  • [21] Network Intrusion Detection Based on Neuro-Fuzzy Classification
    Toosi, Adel Nadjaran
    Kahani, Mohsen
    Monsefi, Reza
    2006 INTERNATIONAL CONFERENCE ON COMPUTING & INFORMATICS (ICOCI 2006), 2006, : 345 - +
  • [22] Runoff estimation using modified adaptive neuro-fuzzy inference system
    Nath, Amitabha
    Mthethwa, Fisokuhle
    Saha, Goutam
    ENVIRONMENTAL ENGINEERING RESEARCH, 2020, 25 (04) : 545 - 553
  • [23] Monthly total sediment forecasting using adaptive neuro fuzzy inference system
    Mahmut Firat
    Mahmud Güngör
    Stochastic Environmental Research and Risk Assessment, 2010, 24 : 259 - 270
  • [24] Retina Recognition System using Adaptive Neuro Fuzzy Inference System
    Borah, Tripti Rani
    Sarma, Kandarpa Kumar
    Talukdar, Pran Hari
    2015 INTERNATIONAL CONFERENCE ON COMPUTER, COMMUNICATION AND CONTROL (IC4), 2015,
  • [25] A new data normalization approach applied to the electromechanical impedance method using adaptive neuro-fuzzy inference system
    Freitas, Fernando Augusto
    Jafelice, Rosana Motta
    da Silva, Jose Waldemar
    Rabelo, Diogo de Souza
    Schroden Nomelini, Quintiliano Siqueira
    Vieira de Moura, Jose dos Reis
    Gallo, Carlos Alberto
    da Cunha, Marcio Jose
    Ramos, Julio Endress
    JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING, 2021, 43 (11)
  • [26] A new data normalization approach applied to the electromechanical impedance method using adaptive neuro-fuzzy inference system
    Fernando Augusto Freitas
    Rosana Motta Jafelice
    José Waldemar da Silva
    Diogo de Souza Rabelo
    Quintiliano Siqueira Schroden Nomelini
    José dos Reis Vieira de Moura
    Carlos Alberto Gallo
    Marcio José da Cunha
    Julio Endress Ramos
    Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2021, 43
  • [27] Monthly total sediment forecasting using adaptive neuro fuzzy inference system
    Firat, Mahmut
    Gungor, Mahmud
    STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2010, 24 (02) : 259 - 270
  • [28] Evaluation of Adaptive Neuro-Fuzzy Inference System with Artificial Neural Network and Fuzzy Logic in Diagnosis of Alzheimer Disease
    Kour, Haneet
    Manhas, Jatinder
    Sharma, Vinod
    PROCEEDINGS OF THE 2019 6TH INTERNATIONAL CONFERENCE ON COMPUTING FOR SUSTAINABLE GLOBAL DEVELOPMENT (INDIACOM), 2019, : 1041 - 1046
  • [29] Vibration for detection and diagnosis bearing faults using adaptive neuro- fuzzy inference system
    Djamila, Bouneb
    Tahar, Bahi
    Hichem, Merabet
    JOURNAL OF ELECTRICAL SYSTEMS, 2018, 14 (01) : 95 - 104
  • [30] Detection of bearing failure in rotating machine using adaptive neuro-fuzzy inference system
    Wadhwani, Sulochana
    Wadhwani, A. K.
    Gupta, S. P.
    Kumar, Vinod
    2006 IEEE INTERNATIONAL CONFERENCE ON POWER ELECTRONIC, DRIVES AND ENERGY SYSTEMS, VOLS 1 AND 2, 2006, : 1059 - +