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Feature Selection Using Rough Set in Intrusion Detection

Anazida Zainal, Mohd Aizaini Maarof, Siti Mariyam Shamsuddin
2006 TENCON 2006 - 2006 IEEE Region 10 Conference  
The purpose of this study is to investigate the effectiveness of Rough Set Theory in identifying important features in building an intrusion detection system.  ...  Most of existing Intrusion Detection Systems use all data features to detect an intrusion.  ...  Their findings showed that rough set classification attained high detection accuracy (using GA) and the feature ranking was fast.  ... 
doi:10.1109/tencon.2006.344210 fatcat:khbvrdsbuze63bxfekbgpwbev4

An Efficient Hybrid Multilevel Intrusion Detection System in Cloud Environment

Partha Ghosh, Chameli Debnath, Dipjyoti Metia, Dr. Ruma Dutta
2014 IOSR Journal of Computer Engineering  
We use Rough Set Theory and Information Gain to select relevant features.  ...  Intrusion Detection System (IDS) plays an important role to identify intrusions by monitoring the activity of the system and alert the user about malicious behaviours and detect attacks.  ...  Intrusion Detection System (IDS) can be classified into two types according to environment of the IDS: Host Based Intrusion Detection System (HIDS) and Network Based Intrusion Detection System (NIDS).  ... 
doi:10.9790/0661-16471626 fatcat:ribh3cmflra35fcyv4hjxrblxa

Intrusion Detection System Based on Genetic Attribute Reduction Algorithm Based on Rough Set and Neural Network

Jan Luo, Huajun Wang, Yanmei Li, Yuxi Lin, Kalidoss Rajakani
2022 Wireless Communications and Mobile Computing  
Therefore, this paper proposes an intrusion detection system based on the combination of genetic attribute reduction algorithm based on rough set and neural network.  ...  At the same time, the intrusion detection system based on the combination of genetic attribute reduction algorithm based on rough set and neural network has significantly improved the detection rate of  ...  Some researches have introduced rough set theory into intrusion detection technology to predict the prediction rule set in system sequence, but it can only be carried out in a small scale [4] .  ... 
doi:10.1155/2022/5031236 fatcat:b5rlsepjfvdlzlye5x5eqojvki

Research on the Precision Instrument Reliability and Anti-interference Mode from the Intrusion Detection Angle based on Rough Set

Jinping Tan, Renqing Li
2016 DEStech Transactions on Social Science Education and Human Science  
In this paper, we conduct research on precision instrument reliability and anti-interference mode from the intrusion detection angle based on rough set.  ...  To enhance the robustness of the mentioned equipment, we consider the integration of the rough set and intrusion detection to modify the corresponding issues that will optimize the traditional methods  ...  In this paper, we conduct research on precision instrument reliability and anti-interference mode from the intrusion detection angle based on rough set.  ... 
doi:10.12783/dtssehs/isetem2016/4481 fatcat:w6afms4rqjg4hedhj6i26hzalq

An Improved Artificial Immune System-Based Network Intrusion Detection by Using Rough Set

Junyuan Shen, Jidong Wang, Hao Ai
2012 Communications and Network  
In this paper, an artificial immune system (AIS) based network intrusion detection scheme is proposed. An optimized feature selection using Rough Set (RS) theory is defined.  ...  With the increasing worldwide network attacks, intrusion detection (ID) has become a popular research topic in last decade.  ...  KDD CUP 99 with Rough Set Theory The data set used in our experiment is the KDD Cup 99 data set, which is the most widely used data set for network-based intrusion detection.  ... 
doi:10.4236/cn.2012.41006 fatcat:uw2rtc35lvavla5irox6edkwye

Intrusion detection using rough set classification

Lian-hua Zhang, Guan-hua Zhang, Lang Yu, Jie Zhang, Ying-cai Bai
2004 Journal of Zhejiang University: Science A  
In this paper, rough set classification (RSC), a modern learning algorithm, is used to rank the features extracted for detecting intrusions and generate intrusion detection models.  ...  Recently machine learning-based intrusion detection approaches have been subjected to extensive researches because they can detect both misuse and anomaly.  ...  In this paper we use rough set classification (RSC) for intrusion detection system (IDS) feature ranking and intrusion detection rules generation.  ... 
doi:10.1631/jzus.2004.1076 pmid:15323002 fatcat:p5h4luf2jva4fmgzzw46356spa

A Survey on SVM Classifiers for Intrusion Detection

R. RavinderReddy, B. Kavya, Y Ramadevi
2014 International Journal of Computer Applications  
In this paper how the support vector machines are used for intrusion detection are described and finally proposed a solution to the inrusion detection system.  ...  Intrusion detection systems aim to identify attacks with a high detection rate and a low false positive.  ...  Host based IDS is installed on each system for monitoring of malicious activities locally .Host-based intrusion detection system (HIDS) uses agent as a sensor on a host that identifies intrusions by analyzing  ... 
doi:10.5120/17294-7779 fatcat:kyj36tilq5bntalx2adtquv3xa

Multi Stage Filter Using Enhanced Adaboost for Network Intrusion Detection

P Natesan
2012 International journal of network security and its applications  
The final stage of the filter is used to detect the infrequent attack which is designed using the enhanced Adaboost algorithm with Naïve Bayes as a base learner.  ...  Weiming Hu et. al., [3] have proposed an Adaboost based algorithm for network intrusion detection.  ...  of the processor and also the attraction detection time.  ... 
doi:10.5121/ijnsa.2012.4308 fatcat:2t2nzkfzordedhha44r24b354m

A SVM and K-means Clustering based Fast and Efficient Intrusion Detection System

Alka Shrivastava, Ram Ratan Ahirwal
2013 International Journal of Computer Applications  
This paper presents a K-means and support vector machine based intrusion detection system.  ...  The intrusion or attack in the computer network is one of the most important issues creating problems for the network managers.  ...  The intrusion detection systems are used to detect such type of attack on a network.  ... 
doi:10.5120/12499-8312 fatcat:ukb3bq6yjjgileq3ha7ra4ohg4

Network intrusion detection by artificial immune system

Junyuan Shen, Jidong Wang
2011 IECON 2011 - 37th Annual Conference of the IEEE Industrial Electronics Society  
In this thesis, an Artificial Immune System (AIS) based intrusion detection is explored.  ...  The main objective of our research is to improve the AIS based Intrusion Detection System's (IDS) performance on detection while keeping its system computing complexity to a low level.  ...  And the performance of the intrusion detection system using rough set is shown in Table 4 -2. As shown in Table 4 -2, the rough set based IDS performs well in detecting the attack on the system.  ... 
doi:10.1109/iecon.2011.6119993 fatcat:n2khqynoxbb23fussr33eqollu

A Rough Set Based Approach To Classify Node Behavior In Mobile Ad Hoc Networks

M. Jain, M.p.s. Bhatia
2014 Journal of Mathematics and Computer Science  
This research investigate the classification of good and bad nodes in the network by using the concept of rough set theory , that can be employed to generate simple rules and to remove irrelevant attributes  ...  Our experiment results reveals that the rough set based approach increases the network capacity and throughput of the network up to 98.9%  ...  Rough Set Theory Rough set theory proposed by Pawlak (1982) is a mathematical tool that's deals with vagueness and uncertainty.  ... 
doi:10.22436/jmcs.011.01.07 fatcat:czdthtbl5zfxxodfwcdotejmlu

Power Intelligent Terminal Intrusion Detection Based on Deep Learning and Cloud Computing

Tong Li, Hai Zhao, Yaodong Tao, Donghua Huang, Chao Yang, Shuheng Xu, Jun Ye
2022 Computational Intelligence and Neuroscience  
It uses a fuzzy integral method to optimize the accuracy of power information network intrusion prediction, and the accuracy reaches 98.11%, with an increase of 0.6%.  ...  Numerous internal and external intrusion attacks have appeared one after another, which has become a major problem affecting the normal operation of the power system.  ...  With the progress of artificial intelligence theory, the intrusion detection technology based on machine learning has also become a research hotspot.  ... 
doi:10.1155/2022/1415713 pmid:35586098 pmcid:PMC9110159 fatcat:gjggxz4nzrbozdxjofw33e64ly

Intelligent feature selection and classification techniques for intrusion detection in networks: a survey

Sannasi Ganapathy, Kanagasabai Kulothungan, Sannasy Muthurajkumar, Muthusamy Vijayalakshmi, Palanichamy Yogesh, Arputharaj Kannan
2013 EURASIP Journal on Wireless Communications and Networking  
In this paper, a survey on intelligent techniques for feature selection and classification for intrusion detection in networks based on intelligent software agents, neural networks, genetic algorithms,  ...  In addition to the survey on existing intelligent techniques for intrusion detection systems, two new algorithms namely intelligent rule-based attribute selection algorithm for effective feature selection  ...  [22] proposed a new agent-based approach for intrusion detection using rough set-based classification technique that uses simple agents.  ... 
doi:10.1186/1687-1499-2013-271 fatcat:njt5czb7mzhuzlnovhha376kpq

Fast intrusion detection based on a non-negative matrix factorization model

Xiaohong Guan, Wei Wang, Xiangliang Zhang
2009 Journal of Network and Computer Applications  
Intrusion detection is a technology for detecting hostile attacks against computer systems from both outside and inside.  ...  Therefore, fast-automated and integrated detection mechanisms and control strategies are required, and intrusion detection systems (IDS) together with intelligent control of network infrastructure consisting  ...  The Rough set theory method is applied to learn a rule set modeling the normal behaviors with small size of training data sets and improved detection accuracy Cai et al. (2003) .  ... 
doi:10.1016/j.jnca.2008.04.006 fatcat:e4onpivo5vhlrdmxl3zmtnvcse

Analysis of KDD CUP 99 Dataset using Clustering based Data Mining

Mohammad Khubeb Siddiqui, Shams Naahid
2013 International Journal of Database Theory and Application  
This paper is an analysis of 10% of KDD cup'99 training dataset based on intrusion detection.  ...  The KDD Cup 99 dataset has been the point of attraction for many researchers in the field of intrusion detection from the last decade.  ...  It is illustrated with an Intrusion Detection Center prototype. In [11] , the authors introduced an intrusion detection system based on Adaptive Resonance Theory (ART) and Rough Set theory.  ... 
doi:10.14257/ijdta.2013.6.5.03 fatcat:shbcidme2vcqldpj75oknmtvay
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