Open AccessJournal Article
Intrusion detection system for cloud computing
TLDR
This work proposes a new multi-threaded distributed cloud IDS model that handles large flow of data packets, analyze them and generate reports efficiently by integrating knowledge and behavior analysis to detect intrusions.Abstract:
Providing security in a distributed system requires more than user authentication with passwords or digital certificates and confidentiality in data transmission. Distributed model of cloud makes it vulnerable and prone to sophisticated distributed intrusion attacks like Distributed Denial of Service (DDOS) and Cross Site Scripting (XSS). To handle large scale network access traffic and administrative control of data and application in cloud, a new multi-threaded distributed cloud IDS model has been proposed. Our proposed cloud IDS handles large flow of data packets, analyze them and generate reports efficiently by integrating knowledge and behavior analysis to detect intrusions. ————————————————————read more
Citations
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A New Threat Intelligence Scheme for Safeguarding Industry 4.0 Systems
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Computational intelligence intrusion detection techniques in mobile cloud computing environments: Review, taxonomy, and open research issues
Shahab Shamshirband,Mahdis Fathi,Anthony T. Chronopoulos,Anthony T. Chronopoulos,Antonio Montieri,Fabio Palumbo,Antonio Pescape +6 more
TL;DR: This paper aims to present a comprehensive survey of intrusion detection systems that use computational intelligence (CI) methods in a (mobile) cloud environment and defines a taxonomy for IDS and classify CI-based techniques into single and hybrid methods.
Journal ArticleDOI
Outlier Dirichlet Mixture Mechanism: Adversarial Statistical Learning for Anomaly Detection in the Fog
TL;DR: An adversarial statistical learning mechanism for anomaly detection, outlier Dirichlet mixture-based ADS (ODM-ADS), which has three new capabilities, which can self-adapt against data poisoning attacks that inject malicious instances in the training phase for disrupting the learning process.
Proceedings ArticleDOI
Intrusion Detection System in Cloud Computing: Challenges and opportunities
TL;DR: This paper provides an overview of different intrusions in cloud and analyzes some existing cloud based intrusion detection systems with respect to their type, positioning, detection time, detection technique, data source and attacks they can detect.
References
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Proceedings ArticleDOI
Controlling data in the cloud: outsourcing computation without outsourcing control
Richard Chow,Philippe Golle,Markus Jakobsson,Elaine Shi,Jessica Staddon,Ryusuke Masuoka,Jesus Molina +6 more
TL;DR: It is argued that with continued research advances in trusted computing and computation-supporting encryption, life in the cloud can be advantageous from a business intelligence standpoint over the isolated alternative that is more common today.
Journal ArticleDOI
Intrusion Detection for Grid and Cloud Computing
TL;DR: The Grid and Cloud Computing Intrusion Detection System integrates knowledge and behavior analysis to detect intrusions.
Proceedings ArticleDOI
Intrusion Detection in the Cloud
TL;DR: Several requirements for deploying IDS in the Cloud are summarized and an extensible IDS architecture for being easily used in a distributed cloud infrastructure is proposed.
Proceedings ArticleDOI
A Cooperative Intrusion Detection System Framework for Cloud Computing Networks
TL;DR: The implementation results indicate that the proposed cooperative IDS system could resist DoS attack and only increases little computation effort compared with pure Snort based IDS but prevents the system from single point of failure attack.
Distributed Cloud Intrusion Detection Model
Irfan Gul,M. Hussain +1 more
TL;DR: This proposed cloud IDS handles large flow of data packets, analyze them and generate reports efficiently and instantly send for information of cloud user and expert advice for cloud service provider’s network misconfigurations through a third party IDS monitoring and advisory service.