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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: | Deep Learning Based Network Intrusion Detection System |
| Authors Name: | Lalitha V G , Sandeep Varma N |
| Unique Id: | IJSDR2209080 |
| Published In: | Volume 7 Issue 9, September-2022 |
| Abstract: | Increase in the network intrusion attacks has raised in the recent few years which has increased the focus on confidentiality and protection. As a result of high technology, internet security attacks are getting complicated and the present detection systems aren’t adequate to deal with this problem. Smart and powerful intrusion disclosure system can be implemented to deal with this issue. In this suggested system, the deep structured learning approaches provide various methods and they can detect the intrusions in the network. CNN and LSTM are used to design a smart detection system that is capable enough to detect different network intrusions. Here we apply CNN and LSTM algorithms and train the model using NSL-KDD dataset. We then evaluate its performance of individual models. Our experimental outcomes show that the execution of the LSTM model is beyond that of the CNN model when tested on NSL-KDD dataset. |
| Keywords: | Deep Learning, Intrusion Detection System, LTSM, CNN |
| Cite Article: | "Deep Learning Based Network Intrusion Detection System", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.7, Issue 9, page no.467 - 472, September-2022, Available :http://www.ijsdr.org/papers/IJSDR2209080.pdf |
| Downloads: | 000337064 |
| Publication Details: | Published Paper ID: IJSDR2209080 Registration ID:201639 Published In: Volume 7 Issue 9, September-2022 DOI (Digital Object Identifier): Page No: 467 - 472 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
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