Journal ArticleDOI
An Improved Intrusion Detection System to Preserve Security in Cloud Environment
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TLDR
A model by which the features are selected on the basis of mutual information gain among correlated features, which leads to a reduced feature set which provides quick learning and thus produces a better IDS that would secure the data in the cloud.Abstract:
Cloud computing, also known as on-demand computing, provides different kinds of services for the users. As the name suggests, its increasing demand makes it prone to various intruders affecting the privacy and integrity of the data stored in the cloud. To cope with this situation, intrusion detection systems (IDS) are implemented in the cloud. An effective IDS constitutes of less time-consuming algorithm with less space complexity and higher accuracy. To do so, the number of features are reduced while maintaining minimal loss of information. In this paper, the authors have proposed a model by which the features are selected on the basis of mutual information gain among correlated features. To achieve this, they first group the features according to the correlativity. Then from each group, the features with the highest mutual information gain in their respective groups are selected. This led them to a reduced feature set which provides quick learning and thus produces a better IDS that would secure the data in the cloud.read more
Citations
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Journal ArticleDOI
Feature Selection Methods Simultaneously Improve the Detection Accuracy and Model Building Time of Machine Learning Classifiers
Saleh Alabdulwahab,Bongkyo Moon +1 more
TL;DR: The authors tested six supervised classifiers on a full NSL-KDD training dataset using 10-fold cross-validation in the Weka tool with and without feature selection/reduction methods to identify more options to outperform and secure classifiers with the highest detection accuracy and lowest model building time.
Journal ArticleDOI
Improved security in cloud using sandpiper and extended equilibrium deep transfer learning based intrusion detection
Journal ArticleDOI
Intrusion detection systems in the cloud computing: A comprehensive and deep literature review
Journal ArticleDOI
An efficient IDS in cloud environment using feature selection based on DM algorithm
TL;DR: The authors proposed a nature-inspired Dolphin Mating (DM) algorithm to determine pertinent features from the dataset and used the NSL-KDD dataset and Kyoto dataset and found that the proposed DM algorithm selects the most relevant feature subset which made the IDS efficient in the Cloud environment.
References
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Journal ArticleDOI
Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy
TL;DR: In this article, the maximal statistical dependency criterion based on mutual information (mRMR) was proposed to select good features according to the maximal dependency condition. But the problem of feature selection is not solved by directly implementing mRMR.
Feature selection based on mutual information: criteria ofmax-dependency, max-relevance, and min-redundancy
TL;DR: This work derives an equivalent form, called minimal-redundancy-maximal-relevance criterion (mRMR), for first-order incremental feature selection, and presents a two-stage feature selection algorithm by combining mRMR and other more sophisticated feature selectors (e.g., wrappers).
Journal ArticleDOI
An Intrusion-Detection Model
TL;DR: A model of a real-time intrusion-detection expert system capable of detecting break-ins, penetrations, and other forms of computer abuse is described, based on the hypothesis that security violations can be detected by monitoring a system's audit records for abnormal patterns of system usage.
Journal ArticleDOI
A framework for constructing features and models for intrusion detection systems
Wenke Lee,Salvatore J. Stolfo +1 more
TL;DR: A novel framework, MADAM ID, for Mining Audit Data for Automated Models for Instrusion Detection, which uses data mining algorithms to compute activity patterns from system audit data and extracts predictive features from the patterns.
Journal ArticleDOI
Network intrusion detection
TL;DR: In this paper, a survey of host-based and network-based intrusion detection systems is presented, and the characteristics of the corresponding systems are identified, and an outline of a statistical anomaly detection algorithm employed in a typical IDS is also included.