International Journal of Emerging Trends & Technology in Computer Science
A Motivation for Recent Innovation & Research
ISSN 2278-6856
www.ijettcs.org
Call for Paper, Published Articles, Indexing Infromation
Title: |
Soft computing and classification approach to Anomaly Based intrusion detection system:
A Survey
|
Author Name: |
Preeti S. Joshi |
Abstract: |
Abstract
Intrusion detection is an eminent upcoming area, as more and
more complex data is being stored and processed in networked
systems. With extensive use of internet service, there is constant
threat of intrusions and misuse. Thus Intrusion Detection
system is most vital component of computer and its network
security. Intrusion Detection System is a software based
monitoring mechanism for a computer network that detects
presence of malevolent activity in the network. IDS system have
gathered consideration by maintaining high safety levels
ensuring trusted and safe announcement of the information
between dissimilar organizations. Intrusion detection systems
classify computer behavior into two main categories: normal
and distrustful activities. Many perspectives for intrusion
detection have been proposed before but none shows acceptable
results so we investigate for better upshot in this field .This
projected approaches represents the intrusion detection in
network using Genetic, Fuzzy and pattern matching Algorithm.
The proposed survey also takes an overview of different type of
classification techniques for Intrusion Detection System (IDS).
We also investigate in these different approaches, their accuracy
as well as false positive ratio
Keywords: Intrusion Detection system, Soft computing,
classification techniques. |
Cite this article: |
Preeti S. Joshi , "
Soft computing and classification approach to Anomaly Based intrusion detection system:
A Survey
" , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS),
Volume 6, Issue 5, September - October 2017 , pp.
027-034 , ISSN 2278-6856.
|