An efficient metaheuristic algorithm based feature selection and recurrent neural network for DoS attack detection in cloud computing environment
出版年份 2020 全文链接
标题
An efficient metaheuristic algorithm based feature selection and recurrent neural network for DoS attack detection in cloud computing environment
作者
关键词
Cloud computing, DoS attack, Crow Search Algorithm, Opposition based learning, Recurrent neural network
出版物
APPLIED SOFT COMPUTING
Volume 100, Issue -, Pages 106997
出版商
Elsevier BV
发表日期
2020-12-13
DOI
10.1016/j.asoc.2020.106997
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Opposition-based learning monarch butterfly optimization with Gaussian perturbation for large-scale 0-1 knapsack problem
- (2018) Yanhong Feng et al. COMPUTERS & ELECTRICAL ENGINEERING
- A scalable distributed machine learning approach for attack detection in edge computing environments
- (2018) Rafał Kozik et al. JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING
- block CV: An r package for generating spatially or environmentally separated folds for k -fold cross-validation of species distribution models
- (2018) Roozbeh Valavi et al. Methods in Ecology and Evolution
- LR-HIDS: logistic regression host-based intrusion detection system for cloud environments
- (2018) Elham Besharati et al. Journal of Ambient Intelligence and Humanized Computing
- Fuzziness based semi-supervised learning approach for intrusion detection system
- (2017) Rana Aamir Raza Ashfaq et al. INFORMATION SCIENCES
- Hybridization of computational intelligence methods for attack detection in computer networks
- (2017) A. Branitskiy et al. Journal of Computational Science
- Service resizing for quick DDoS mitigation in cloud computing environment
- (2016) Gaurav Somani et al. Annals of Telecommunications
- A survey on the application of recurrent neural networks to statistical language modeling
- (2015) Wim De Mulder et al. COMPUTER SPEECH AND LANGUAGE
- Distributed denial of service attacks in software-defined networking with cloud computing
- (2015) Qiao Yan et al. IEEE COMMUNICATIONS MAGAZINE
- A new bio-inspired optimisation algorithm: Bird Swarm Algorithm
- (2015) Xian-Bing Meng et al. JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE
- A method of DDoS attack detection using HTTP packet pattern and rule engine in cloud computing environment
- (2014) Junho Choi et al. SOFT COMPUTING
- Can We Beat DDoS Attacks in Clouds?
- (2013) Shui Yu et al. IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
- Minimal complexity attack classification intrusion detection system
- (2012) G. Gowrison et al. APPLIED SOFT COMPUTING
- A survey on gaps, threat remediation challenges and some thoughts for proactive attack detection in cloud computing
- (2012) Md. Tanzim Khorshed et al. Future Generation Computer Systems-The International Journal of eScience
- A survey of intrusion detection techniques in Cloud
- (2012) Chirag Modi et al. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
- A survey on security issues and solutions at different layers of Cloud computing
- (2012) Chirag Modi et al. JOURNAL OF SUPERCOMPUTING
- Mitigating DDoS attacks with transparent and intelligent fast-flux swarm network
- (2011) Ruiping Lua et al. IEEE NETWORK
- Cloud security defence to protect cloud computing against HTTP-DoS and XML-DoS attacks
- (2010) Ashley Chonka et al. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
- A survey on security issues in service delivery models of cloud computing
- (2010) S. Subashini et al. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
- A note on “Opposition versus randomness in soft computing techniques” [Appl. Soft Comput. 8 (2) (2008) 906–918]
- (2009) M. Ventresca et al. APPLIED SOFT COMPUTING
- Opposition versus randomness in soft computing techniques
- (2007) Shahryar Rahnamayan et al. APPLIED SOFT COMPUTING
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreAdd your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload Now