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Feb 2024 - Volume 16, Issue 1
Deadline: 15 Jan 2025
Publication: 20 Feb 2025
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Deadline: 15 Mar 2024
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ABSTRACT
| Title |
: |
Adaptive Genetic Algorithm Model for Intrusion Detection |
| Authors |
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K. S. Anil Kumar, Dr. V. Nanda Mohan |
| Keywords |
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Intrusion Detection System (IDS), K-Means Clustering, Neuro - Genetic, DARPA dataset |
| Issue Date |
: |
Aug-Sep 2012 |
| Abstract |
: |
Intrusion detection systems are intelligent systems designed to identify and prevent the misuse of computer networks and systems. Various approaches to Intrusion Detection are currently being used, but they are relatively ineffective. Thus the emerging network security systems need be part of the life system and this is possible only by embedding knowledge into the network. The Adaptive Genetic Algorithm Model - IDS comprising of K-Means clustering Algorithm, Genetic Algorithm and Neural Network techniques. The technique is tested using multitude of background knowledge sets in DARPA network traffic datasets. |
| Page(s) |
: |
595-599 |
| ISSN |
: |
0976-5166 |
| Source |
: |
Vol. 3, No.4 |
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