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Host Based Intrusion Detection Using Data Mining Methodologies

M Naga Surya Lakshmi1 , K V N Sunitha2

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-8 , Page no. 992-998, Aug-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i8.992998

Online published on Aug 31, 2018

Copyright © M Naga Surya Lakshmi, K V N Sunitha . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: M Naga Surya Lakshmi, K V N Sunitha, “Host Based Intrusion Detection Using Data Mining Methodologies,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.8, pp.992-998, 2018.

MLA Style Citation: M Naga Surya Lakshmi, K V N Sunitha "Host Based Intrusion Detection Using Data Mining Methodologies." International Journal of Computer Sciences and Engineering 6.8 (2018): 992-998.

APA Style Citation: M Naga Surya Lakshmi, K V N Sunitha, (2018). Host Based Intrusion Detection Using Data Mining Methodologies. International Journal of Computer Sciences and Engineering, 6(8), 992-998.

BibTex Style Citation:
@article{Lakshmi_2018,
author = {M Naga Surya Lakshmi, K V N Sunitha},
title = {Host Based Intrusion Detection Using Data Mining Methodologies},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {8 2018},
volume = {6},
Issue = {8},
month = {8},
year = {2018},
issn = {2347-2693},
pages = {992-998},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2806},
doi = {https://doi.org/10.26438/ijcse/v6i8.992998}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i8.992998}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2806
TI - Host Based Intrusion Detection Using Data Mining Methodologies
T2 - International Journal of Computer Sciences and Engineering
AU - M Naga Surya Lakshmi, K V N Sunitha
PY - 2018
DA - 2018/08/31
PB - IJCSE, Indore, INDIA
SP - 992-998
IS - 8
VL - 6
SN - 2347-2693
ER -

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Abstract

In today’s computing world there is an inconceivable growth in the usage of computers over different networks and domains, which in turn increases the security threats in terms of intrusions. An intrusion can be either internal or external and the conventional methods used in the detection of intrusion are failed to meet the necessities of preventing and detecting threats or intrusions. In this paper, Data Mining methodologies are combined to handle some of the problems like data Preparation, pre-processing of the data, data classification and Intrusion Detection. The definitive role of IDS is to recognize threats or attacks in contrast to computing schemes. The intrusion detection system is one of the vital networks shielding device or software for safeguarding computing schemes and it is capable to discover and to examine network traffic data packets. This research paper is developed situated on advanced snort rules have been developed. The main goal of this research paper is to detect fraudulent network traffic.

Key-Words / Index Term

Intrusion Detection System, Intrusion Prevention System, Snort

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