PERFORMANCE ANALYSIS OF MACHINE LEARNING TECHNIQUES FOR INTRUSION DETECTION SYSTEM

被引:0
|
作者
Jadhav, Abhijit D. [1 ,2 ]
Pellakuri, Vidyullatha [1 ]
机构
[1] Koneru Lakshmaiah Educ Fdn, Dept Comp Sci & Engn, Vaddeswaram, AP, India
[2] Dr DY Patil Inst Technol, Dept Comp Engn, Pune 18, Maharashtra, India
关键词
accuracy; efficiency; intrusion detection; machine learning techniques; survey;
D O I
10.1109/iccubea47591.2019.9128917
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
It is very important to protect organizations assets and resources over the network from attackers. Much of the work is already been done in the past by different researchers from different corners of the universe. Many of them have been proved successful over the years. The work is related to detection of such intruders prior any damage being done by them to important assets. The systems used for intruder detection are called as Intrusion Detection Systems (IDS). Now a days, solving problems with data acquisition is very effective, which is nothing but the machine learning approach. Same approach can be used for implementation of IDS. In fact, many researchers have done the lot of work in IDS implementations by using different machine learning techniques. There are number of machine learning techniques which are proving and producing better results for in different areas for problem solutions. Here, we will try to find and compare the different results obtained by researchers with different machine learning techniques for IDS implementation.
引用
收藏
页数:9
相关论文
共 50 条
  • [41] Advancing Network Intrusion Detection Systems with Machine Learning Techniques
    Benmalek, Mourad
    Haouam, Kamel-Dine
    ADVANCES IN ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING, 2024, 4 (03): : 2575 - 2592
  • [42] Machine Learning Techniques for Enhanced Intrusion Detection in IoT Security
    Hakami, Hanadi
    Faheem, Muhammad
    Bashir Ahmad, Majid
    IEEE ACCESS, 2025, 13 : 31140 - 31158
  • [43] Intrusion detection based on Machine Learning techniques in computer networks
    Dina, Ayesha S.
    Manivannan, D.
    INTERNET OF THINGS, 2021, 16
  • [44] Intrusion Detection in SCADA systems using Machine Learning Techniques
    Maglaras, Leandros A.
    Jiang, Jianmin
    2014 SCIENCE AND INFORMATION CONFERENCE (SAI), 2014, : 626 - 631
  • [45] Comparative study of supervised machine learning techniques for intrusion detection
    Gharibian, Farnaz
    Ghorbani, Ali A.
    CNSR 2007: PROCEEDINGS OF THE FIFTH ANNUAL CONFERENCE ON COMMUNICATION NETWORKS AND SERVICES RESEARCH, 2007, : 350 - +
  • [46] Review on Network Intrusion Detection Techniques using Machine Learning
    Shashank, K.
    Balachandra, Mamatha
    PROCEEDINGS OF 2018 IEEE DISTRIBUTED COMPUTING, VLSI, ELECTRICAL CIRCUITS AND ROBOTICS (DISCOVER), 2018, : 104 - 109
  • [47] Comparative Analysis of Intrusion Detection System Using Machine Learning and Deep Learning Algorithms
    Note J.
    Ali M.
    Annals of Emerging Technologies in Computing, 2022, 6 (03) : 19 - 36
  • [48] A Comprehensive Review and Meta-Analysis on Applications of Machine Learning Techniques in Intrusion Detection
    Chattopadhyay, Manojit
    Sen, Rinku
    Gupta, Sumeet
    AUSTRALASIAN JOURNAL OF INFORMATION SYSTEMS, 2018, 22
  • [49] IoBT Intrusion Detection System using Machine Learning
    Alkanjr, Basmh
    Alshammari, Thamer
    2023 IEEE 13TH ANNUAL COMPUTING AND COMMUNICATION WORKSHOP AND CONFERENCE, CCWC, 2023, : 886 - 892
  • [50] Network intrusion detection system: A machine learning approach
    Panda, Mrutyunjaya
    Abraham, Ajith
    Das, Swagatam
    Patra, Manas Ranjan
    INTELLIGENT DECISION TECHNOLOGIES-NETHERLANDS, 2011, 5 (04): : 347 - 356