Journal ArticleDOI
Review: An intrusion detection and prevention system in cloud computing: A systematic review
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TLDR
This paper surveys, explores and informs researchers about the latest developed IDPSs and alarm management techniques by providing a comprehensive taxonomy and investigating possible solutions to detect and prevent intrusions in cloud computing systems.About:
This article is published in Journal of Network and Computer Applications.The article was published on 2013-01-01. It has received 369 citations till now. The article focuses on the topics: Cloud computing & Cloud computing security.read more
Citations
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Journal ArticleDOI
Survey of intrusion detection systems: techniques, datasets and challenges
TL;DR: A taxonomy of contemporary IDS is presented, a comprehensive review of notable recent works, and an overview of the datasets commonly used for evaluation purposes are presented, and evasion techniques used by attackers to avoid detection are presented.
Journal ArticleDOI
Security issues in cloud environments: a survey
TL;DR: This paper surveys the works on cloud security issues, making a comprehensive review of the literature on the subject and proposes a taxonomy for their classification, addressing several key topics, namely vulnerabilities, threats, and attacks.
Journal ArticleDOI
NICE: Network Intrusion Detection and Countermeasure Selection in Virtual Network Systems
TL;DR: This work proposes a multiphase distributed vulnerability detection, measurement, and countermeasure selection mechanism called NICE, which is built on attack graph-based analytical models and reconfigurable virtual network-based countermeasures to significantly improve attack detection and mitigate attack consequences.
Journal ArticleDOI
Evaluation of machine learning classifiers for mobile malware detection
TL;DR: An alternative solution to evaluating malware detection using the anomaly-based approach with machine learning classifiers is proposed, which revealed that the k-nearest neighbor classifier efficiently detected the latest Android malware with an 84.57 % true-positive rate higher than other classifiers.
Journal ArticleDOI
A cybersecurity framework to identify malicious edge device in fog computing and cloud-of-things environments
TL;DR: Proposed cybersecurity framework uses Markov model, Intrusion Detection System (IDS), and Virtual Honeypot Device (VHD) to identify malicious edge device in fog computing environment and results indicated that proposed cybersecurity framework is successful in identifying the malicious device as well as reducing the false IDS alarm rate.
References
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Journal ArticleDOI
Anomaly detection: A survey
TL;DR: This survey tries to provide a structured and comprehensive overview of the research on anomaly detection by grouping existing techniques into different categories based on the underlying approach adopted by each technique.
Proceedings ArticleDOI
Cloud Computing and Grid Computing 360-Degree Compared
TL;DR: In this article, the authors compare and contrast cloud computing with grid computing from various angles and give insights into the essential characteristics of both the two technologies, and compare the advantages of grid computing and cloud computing.
Journal ArticleDOI
Review: A survey on security issues in service delivery models of cloud computing
S. Subashini,V. Kavitha +1 more
TL;DR: A survey of the different security risks that pose a threat to the cloud is presented and a new model targeting at improving features of an existing model must not risk or threaten other important features of the current model.
Journal ArticleDOI
Data fusion
Jens Bleiholder,Felix Naumann +1 more
TL;DR: This article places data fusion into the greater context of data integration, precisely defines the goals of data fusion, namely, complete, concise, and consistent data, and highlights the challenges of data Fusion.
Journal ArticleDOI
Anomaly-based network intrusion detection: Techniques, systems and challenges
TL;DR: The main challenges to be dealt with for the wide scale deployment of anomaly-based intrusion detectors, with special emphasis on assessment issues are outlined.