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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016 open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15 |
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| Paper Title: | Semi supervised machine learning approach for probe attack |
| Authors Name: | A.Hasini , S.Keerthi Priya , V. Srilakshmi , K.Anuranjani |
| Unique Id: | IJSDR2304093 |
| Published In: | Volume 8 Issue 4, April-2023 |
| Abstract: | The quick spread of computer networks has altered how network security is seen. The ease of accessibility makes computer networks vulnerable to many hacking attacks. There are various and possibly catastrophic threats to networks. Researchers have so far created intrusion detection systems (IDS) that can recognise assaults in a variety of situations. There are several techniques that may be used to identify abuse and anomalies. Since various types of ecosystems are best served by different techniques, many of the technologies presented are complimentary to one another. Several intrusion detection systems have been developed to defend against these threats used. The Intrusion Detection System (IDS) is a system that gathers and examines network data to find various assaults conducted against network components. We built the model using the KDDcup99 data set. In this article, a three-layer architecture for probe attack detection is suggested. Dimensionality reduction is accomplished via Principal Component Analysis. Duplicate samples were also taken out of the training data set. Finally, we used a line chart to compare the effectiveness of each classifier. The new intrusion detection technology presented in this research is utilised to survey and categorise them. The detection theory and a few operational components of intrusion detection make up the taxonomy |
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| Cite Article: | "Semi supervised machine learning approach for probe attack", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 4, page no.510 - 514, April-2023, Available :http://www.ijsdr.org/papers/IJSDR2304093.pdf |
| Downloads: | 000337209 |
| Publication Details: | Published Paper ID: IJSDR2304093 Registration ID:205016 Published In: Volume 8 Issue 4, April-2023 DOI (Digital Object Identifier): Page No: 510 - 514 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
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