|
|||||||||||||||
|
INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
||||||||||||||
Issue: May 2024
Volume 9 | Issue 5
Review Result and Publication of Paper within : 2-3 days
Click Here For more DetailsFor Authors
Forms / Download
Published Issue Details
Editorial Board
Other IMP Links
Facts & Figure
Impact Factor : 8.76
Issue per Year : 12
Volume Published : 9
Issue Published : 96
Article Submitted :
Article Published :
Total Authors :
Total Reviewer :
Total Countries :
Indexing Partner
Join RMS/Earn 300
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
Published Paper Details
|
|
| Paper Title: | Detection and Elimination of Network Anomaly in SDN using Trust Analysis |
| Authors Name: | Santhosh Rajan , Shanmugam |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_195077
|
| Published Paper Id: | IJNRD2305335 |
| Published In: | Volume 8 Issue 5, May-2023 |
| DOI: | http://doi.one/10.1729/Journal.34207 |
| Abstract: | The necessity for networking and data exchange has dramatically increased in the modern world. Network security is necessary given the rapid development and globalization of information technology. Although they may offer some amount of security, firewalls never warn administrators of impending assaults. A trustworthy detection system is required to locate such aberrant network packet behavior in order to increase efficiency and accuracy. As a result of how quickly today's network environment is evolving, the network is constantly at risk from new sorts of attacks. Therefore, regular updates to the network administration system are required for upgrading the security level. Intrusion Detection Systems is one of the network packet monitoring systems (IDS). The proposed model was created using a machine learning approach to identify malicious network packet activity. KDD-99 dataset is utilized for that. The dataset is first normalized to reduce calculation complexity, and then further features are reduced using a Deep Neural Network technique. Only effective features can be employed for harmful behavior identification, according to the reduced features. According to the results analysis, DNN works best when choosing more than 15 features, whereas co-relation performs best when choosing less than 15. The k-mean clustering algorithm is used to accomplish data clustering after feature reduction. Deep Neural Network, are designed for classification of dataset into five attack categories i.e. DOS, U2R, R2L, Probe and Normal. As compared to some other multilevel classifier work the proposed algorithm proves its efficiency in terms of high accuracy, high detection rate and False Alarm Rate (FAR). |
| Keywords: | SDN, Random Forest Classifier, Intrusion Detection System, KNN Clustering |
| Cite Article: | "Detection and Elimination of Network Anomaly in SDN using Trust Analysis", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 5, page no.d247-d252, May-2023, Available :http://www.ijnrd.org/papers/IJNRD2305335.pdf |
| Downloads: | 000118750 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
| Publication Details: |
Published Paper ID:IJNRD2305335 Registration ID: 195077 Published In: Volume 8 Issue 5, May-2023 DOI (Digital Object Identifier): http://doi.one/10.1729/Journal.34207 Page No: d247-d252 Country: Cuddalore, Tamil Nadu, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2305335 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2305335 |
| Share Article: |
|
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
Major Indexing from www.ijnrd.org
| Semantic Scholar | Microsaoft Academic | ORCID | Zenodo |
| Google Scholar | ResearcherID Thomson Reuters | Mendeley : reference manager | Academia.edu |
| arXiv.org : cornell university library | Research Gate | CiteSeerX | PUBLON |
| DRJI | SSRN | Scribd | DocStoc |
ISSN Details
 |
 |
|
ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016
DOI (A digital object identifier)
Conference
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Important Details
Social Media
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Join RMS/Earn 300
| Copyright © 2024 - All Rights Reserved - IJNRD |
Facebook Twitter Instagram LinkedIn