Results 51 to 60 of about 7,004,502 (187)
Sensors, 2022 As the range of security attacks increases across diverse network applications, intrusion detection systems are of central interest. Such detection systems are more crucial for the Internet of Things (IoT) due to the voluminous and sensitive data it ...
Shapla Khanam +3 more
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, 2006 Network intrusion detection is the problem of detecting unauthorised use of, or access to, computer systems over a network. One approach is anomaly detection, where deviations from a model of normal network activity are reported.
Powers, Simon T., He, Jun
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Network intrusion detection system using supervised learning paradigm
Scientific African, 2020 Internet has positively changed social, political and economic structures and in many ways obviating geographical boundaries. The enormous contributions of Internet to business transactions coupled with its ease of use has resulted in increased number of
J. Olamantanmi Mebawondu +3 more
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LOGICAL TIME AND SPACE OF THE NETWORK INTRUSION
Studia Universitatis Babes-Bolyai: Series Informatica, 2017 Nowadays, one of the biggest threats for modern computer networks are the cyber attacks. One of the possible ways how to increase the level of computer networks security is a deployment of a network intrusion detection system.
Daniel MIHÁLYI +2 more
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Analysis of Network Intrusion Detection Based on Semi-Supervised and SS-DGM
IEEE AccessThe rapid advancement of technology has made network security a hot topic of concern for researchers worldwide. Therefore, to improve the accuracy and real-time response capability of network intrusion detection systems, and to effectively detect and ...
Xiao Yu +5 more
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Active Learning for Network Intrusion Detection [PDF]
, 2021 Network operators are generally aware of common attack vectors that they defend against. For most networks the vast majority of traffic is legitimate. However new attack vectors are continually designed and attempted by bad actors which bypass detection and go unnoticed due to low volume.
openaire +2 more sources
Application of bagging, boosting and stacking to intrusion detection
, 2012 This paper investigates the possibility of using ensemble algorithms to improve the performance of network intrusion detection systems. We use an ensemble of three different methods, bagging, boosting and stacking, in order to improve the accuracy and ...
Syarif, Iwan +3 more
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Machine Learning for Intrusion Detection: Modeling the Distribution Shift [PDF]
, 2010 This paper addresses two important issue that arise in formulating and solving computer intrusion detection as a machine learning problem, a topic that has attracted considerable attention in recent years including a community wide competition using a ...
Saunders, Craig +5 more
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An immunological approach to intrusion detection [PDF]
, 2000 This paper presents an examination of intrusion detection schemes. It discusses traditional views of intrusion detection, and examines the more novel, but perhaps more effective, approach to intrusion detection as modeled on the human immune system ...
Watkins, A., Andrew Watkins
core
Application of Self-Organizing Feature Map Neural Network Based on K-means Clustering in Network Intrusion Detection [PDF]
, 2019 Due to the widespread use of the Internet, customer information is vulnerable to computer systems attack, which brings urgent need for the intrusion detection technology.
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