Measuring Detection of Signature On Enterprise Computer Network

Author:

Alviana S,Sumitra I D

Abstract

Abstract The purpose of this study is to measure the comparative success rate methods of signature-based anomaly based on enterprise computer network attack detected. The application of information technology in many fields often cause the occurrence of attacks and threats that lead to data loss, the crippled system, and destruction of the system. To address these threats required the presence of early detection against any threats that occur at the enterprise computer network system. Early detection function to minimize and prevent the loss of the more extensive system. Methods used in the detection of the threat that is signature based and anomaly-based method. Both methods are used for detection of any threats to the network system, then that method will be between the two measured how many threats can be detected by both methods, and measure the level of success detection. The results obtained in this study, Method of Anomaly Based successfully detect 89.66% attack, while the method Signature based successfully detected 91.87% attack. If the results of the great early attack detection, then the security level of the network are also great and can reduce the risk posed by a threat.

Publisher

IOP Publishing

Subject

General Medicine

Reference10 articles.

1. Performance improvement of intrusion detection with fusion of multiple sensors;Shah;Complex & Intelligent Systems,2017

2. Defending yourself: The role of intrusion detection systems;McHugh;IEEE software,2000

3. A Survey on Anomaly Based Host Intrusion Detection System;Jose;Journal of Physics: Conference Series,2018

4. Intrusion detection system: A comprehensive review;Liao;Journal of Network and Computer Applications,2013

5. Policy and network-based intrusion detection system for IPv6-enabled wireless sensor networks;Amaral,2014

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Pollen harvest monitoring system using internet of things;SIXTH INTERNATIONAL CONFERENCE OF MATHEMATICAL SCIENCES (ICMS 2022);2023

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3