A Comprehensive Analysis and Study in Intrusion Detection System Using k-NN Algorithm

Wagh, Sharmila K.; Neelwarna, Gaurav; Kolhe, Satish R.

doi:10.1007/978-3-642-35455-7_14

Cited by 2 publications

(2 citation statements)

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“…To detect the intrusion, a KNN based method was employed by the authors (Wagh, Neelwarna, & Kolhe, 2012), they claimed that the outcome of KNN is more efficient then the earlier existing methods (Wagh, Neelwarna, & Kolhe, 2012). In another work, modified version of SVM that employ the bat algorithm to synchronize the feature selection was proposed by (Chen, Zhichun, Xia, & Liu, 2013).…”

Section: Noteworthy Contribution Related To This Work Has Been Presen...mentioning

confidence: 99%

An Efficient Method to Decide the Malicious Traffic

Kumar

Singh

Kumar

et al. 2023

International Journal of Decision Support System Technology

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To address the high rate of false alarms, this article proposed a voting-based method to efficiently predict intrusions in real time. To carry out this study, an intrusion detection dataset from UNSW was downloaded and preprocessed before being used. Given the number of features at hand and the large size of the dataset, performance was poor while accuracy was low. This low prediction accuracy led to the generation of false alerts, consequently, legitimate alerts used to pass without an action assuming them as false. To deal with large size and false alarms, the proposed voting-based feature reduction approach proved to be highly beneficial in reducing the dataset size by selecting only the features secured majority votes. Outcome collected prior to and following the application of the proposed model were compared. The findings reveal that the proposed approach required less time to predict, at the same time predicted accuracy was higher. The proposed approach will be extremely effective at detecting intrusions in real-time environments and mitigating the cyber-attacks.

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Section: Noteworthy Contribution Related To This Work Has Been Presen...mentioning

confidence: 99%

An Efficient Method to Decide the Malicious Traffic

Kumar

Singh

Kumar

et al. 2023

International Journal of Decision Support System Technology

View full text Add to dashboard Cite

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“…mixed design and implementation, difficulties in development, exposing internal implementation details, etc.) [Wag12]. Any SOAP-based WS project takes at least 2 years in defining the SOAP WS layer, deploying those services, and standardizing the interfaces.…”

Section: Chapter 1: Introductionmentioning

confidence: 99%

MAMSaaS: Mashup Architecture with Modeling and Simulation as a Service

Wang¹

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In recent years, developing Modeling and Simulation (M&S) applications has become more and more complex. New technologies, like Web Services (WS) and Cloud computing, have been recently used in Modeling and Simulation (M&S). However, developing M&S applications using these technologies is still a complicated process. The reasons for this include: 1) it is hard to develop web services for varied M&S resources;2) it is complicated to deploy M&S resources in the Cloud; 3) it is hard to integrate with varied M&S services; 4) it is complex to identify and select resources and services based on their meaning. In this research, we aim to simplify the development and integration of M&S applications using web technologies by solving the issues mentioned above. To do so, we propose the Mashup Architecture with Modeling and Simulation as a Service (termed MAMSaaS). MAMSaaS is a layered and lightweight M&S application development approach. It has five layers, which are Cloud, Box, Wiring, Mashup, and Tag Ontology Layers. It has a simplified life cycle to develop, deploy, identify, select, integrate and execute varied M&S resources as services in the Cloud. In the Cloud Layer, we developed CloudRISE middleware to expose RESTful Modeling and Simulation as a Service (MSaaS) for varied M&S resources; in addition, we propose new methods using Cloud computing and Experimental Framework concept to simplify the deployment of experiment environment. In the Box, Wiring and Mashup Layers, we present a new method based on mashup technologies to simplify the integration, execution and visualization of M&S applications. In the Tag Ontology Layer, we propose a new semantic selection approach using tag-mining and ontology-learning technologies, to identify and select M&S resources based on their meanings. iv

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A Comprehensive Analysis and Study in Intrusion Detection System Using k-NN Algorithm

Cited by 2 publications

References 10 publications

An Efficient Method to Decide the Malicious Traffic

An Efficient Method to Decide the Malicious Traffic

MAMSaaS: Mashup Architecture with Modeling and Simulation as a Service

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