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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: | Prediction of network attacks using supervised machine learning |
| Authors Name: | B.Sai Giridhar , A.Mallikarjuna , N.Naresh , K.Rakesh |
| Unique Id: | IJSDR2304381 |
| Published In: | Volume 8 Issue 4, April-2023 |
| Abstract: | With the evolution in wireless communication, there are many security threats over the internet. The intrusion detection system (IDS) helps to find the attacks on the system and the intruders are detected. Previously various machine learning (ML) techniques are applied on the IDS and tried to improve the results on the detection of intruders and to increase the accuracy of the IDS. This paper has proposed an approach to develop efficient IDS by using the principal component analysis (PCA) and the random forest classification algorithm. Where the PCA will help to organise the dataset by reducing the dimensionality of the dataset and the random forest will help in classification. Results obtained states that the proposed approach works more efficiently in terms of accuracy as compared to other techniques like Naïve Bayes, and Decision Tree. |
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| Cite Article: | "Prediction of network attacks using supervised machine learning", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 4, page no.2451 - 2475, April-2023, Available :http://www.ijsdr.org/papers/IJSDR2304381.pdf |
| Downloads: | 000337070 |
| Publication Details: | Published Paper ID: IJSDR2304381 Registration ID:205757 Published In: Volume 8 Issue 4, April-2023 DOI (Digital Object Identifier): Page No: 2451 - 2475 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
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