An Intrusion Detection System Using Modified-Firefly Algorithm in Cloud Environment

IF 0.6 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Partha Ghosh, D. Sarkar, Joy Sharma, S. Phadikar
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引用次数: 9

Abstract

The present era is being dominated by cloud computing technology which provides services to the users as per demand over the internet. Satisfying the needs of huge people makes the technology prone to activities which come up as a threat. Intrusion detection system (IDS) is an effective method of providing data security to the information stored in the cloud which works by analyzing the network traffic and informs in case of any malicious activities. In order to control high amount of data stored in cloud, data is stored as per relevance leading to distributed computing. To remove redundant data, the authors have implemented data mining process such as feature selection which is used to generate an optimum subset of features from a dataset. In this paper, the proposed IDS provides security working upon the idea of feature selection. The authors have prepared a modified-firefly algorithm which acts as a proficient feature selection method and enables the NSL-KDD dataset to consume less storage space by reducing dimensions as well as less training time with greater classification accuracy.
基于改进萤火虫算法的云环境入侵检测系统
当今时代是由云计算技术主导的,云计算技术通过互联网为用户提供按需服务。为了满足庞大人群的需求,这项技术很容易出现威胁活动。入侵检测系统(IDS, Intrusion detection system)是一种通过分析网络流量,及时发现恶意活动,为存储在云中的信息提供数据安全保障的有效方法。为了控制存储在云中的大量数据,数据按相关性存储,从而实现分布式计算。为了去除冗余数据,作者实现了数据挖掘过程,如特征选择,用于从数据集中生成最优的特征子集。在本文中,提出的IDS基于特征选择的思想提供安全工作。作者准备了一种改进的萤火虫算法,作为一种熟练的特征选择方法,使NSL-KDD数据集通过降维消耗更少的存储空间和更少的训练时间,具有更高的分类精度。
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来源期刊
International Journal of Digital Crime and Forensics
International Journal of Digital Crime and Forensics COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-
CiteScore
2.70
自引率
0.00%
发文量
15
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