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

被引:9
|
作者
Ghosh, Partha [1 ]
Sarkar, Dipankar [2 ]
Sharma, Joy [1 ]
Phadikar, Santanu [3 ]
机构
[1] Netaji Subhash Engn Coll, Kolkata, W Bengal, India
[2] Tata Consultancy Serv, Mumbai, Maharashtra, India
[3] Maulana Abul Kalam Azad Univ Technol, Dept Comp Sci & Engn, Kolkata, W Bengal, India
关键词
Cloud Computing; Feature Selection; Firefly Algorithm (FA); Intrusion Detection System (IDS); NSL-KDD Dataset; Particle Swarm Optimization (PSO); CLASSIFICATION;
D O I
10.4018/IJDCF.2021030105
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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.
引用
收藏
页码:77 / 93
页数:17
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