INTRUSION DETECTION SYSTEM BASED ON GENETIC ALGORITHM: A SURVEY
Author(s):
KAMLESH PATEL, Prabhakar Sharma
Keywords:
Intrusion Detection, Genetic Algorithm, NSL-kdd dataset
Abstract
The intrusion detection system is becoming a difficult task. Since the increasing amount of systems provides larger access to outsiders and makes it easier for offender to avoid identification. Intrusion detection systems are detecting unauthorized access to a system. By This paper presenting a survey on intrusion detection techniques that use genetic rule approach or genetic algorithm. Currently Intrusion Detection System (IDS) that is outlined as an answer of system security is used to spot the abnormal activities during a system or network. To this point completely different approaches are utilized in intrusion detections, however anyone of the systems isn't entirely ideal. Hence, the hunt of improved technique goes on. During this progression, here even have designed an Intrusion Detection System (IDS), by applying genetic algorithm (GA) to expeditiously observe numerous styles of the intrusive activities among a network. The experiments and evaluations of the planned intrusion detection system are performed with the NSL KDD intrusion detection benchmark dataset. The experimental results clearly show that the planned system achieved higher accuracy rate in distinctive whether or not the records are traditional or abnormal ones and obtained cheap detection rate.
Article Details
Unique Paper ID: 143976

Publication Volume & Issue: Volume 3, Issue 4

Page(s): 285 - 290
Article Preview & Download


Share This Article

Conference Alert

NCSST-2021

AICTE Sponsored National Conference on Smart Systems and Technologies

Last Date: 25th November 2021

SWEC- Management

LATEST INNOVATION’S AND FUTURE TRENDS IN MANAGEMENT

Last Date: 7th November 2021

Go To Issue



Call For Paper

Volume 8 Issue 4

Last Date 25 September 2021

About Us

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org

Social Media

Google Verified Reviews

Contact Details

Telephone:6351679790
Email: editor@ijirt.org
Website: ijirt.org

Policies