Kernel Based Intrusion Detection Using Data Mining Techniques

Authors(1) :-Shivalingari Bhanu Sree

From the onset of internet arrangement, protection menaces normally recognized as intrusions has return to be a highly important and demanding issue in internet arrangements, knowledge and information system. In this system to overcome these menaces every time a detection arrangement was requested because of extreme development in networks. within the growth of the arrangement, attackers came to be stronger and every single amount compromises the protection of the network.Hence a requirement of the Intrusion Detection arrangement came to be a very important and important instrument in net security. Detection and hindrance of such aggressions loud intrusions typically depends on the talent and potency of Intrusion Detection Arrangement (IDS). In this apporch number of component has been directed for using the methods, these systems have their own advantages and deficiencies”. Here mainly focusing on different classification methods.

Authors and Affiliations

Shivalingari Bhanu Sree
PG Scholar, Department of IT, VNR Vignan Jyothi Institute of Engineering and Technology, Hyderabad , TS, India

Intrusion Detection, Anomaly Detection, Misuse Detection, KDD Cup99

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Publication Details

Published in : Volume 3 | Issue 1 | January-February 2018
Date of Publication : 2018-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 268-276
Manuscript Number : CSEIT183178
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Shivalingari Bhanu Sree, "Kernel Based Intrusion Detection Using Data Mining Techniques", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 1, pp.268-276, January-February-2018.
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