In this paper, we present a novel method for the detection of outlier in intrusion detection system. The proposed detection algorithm, are called hybrid algorithm. It is combination of two algorithm k-mean and boxplot. Experimental results demonstrate to be superior to existing SCF algorithm. One of the most common problems in existing SCF technique detection techniques is that such as ignoring dependency among categorical variables, handling data streams and mixed data sets. Moreover, identifying number of outliers in advance is an impractical issue in the SCF algorithm and other outlier identification techniques. This paper investigates the performances of boxplot-mean method for detecting different types of abnormal data. Keywords: Outli...
In recent years, intrusion detection has emerged as an important technique for network security. Mac...
AbstractIn recent research, outlier mining has been widely used in areas such as telecommunication, ...
Intrusion detection is crucial in computer network security issues; therefore, this work is aimed at...
In this paper, we present a novel method for the detection of outlier in intrusion detection system....
Outlier is a data point that deviates too much from the rest of dataset. Most of real-world dataset ...
Outlier Detection is a technique to detect anomalous events or outliers during analysis of the data ...
The outlier detection in the field of data mining and Knowledge Discovering from Data (KDD) is captu...
Data mining has the vital task of Outlier detection which aims to detect an outlier from given datas...
Abstract- Outlier detection is an active area for research in data set mining community. Finding out...
The tremendous advancement and increase in usage of internet have increased the number of intruders ...
Outliers identification is essential in data analysis since it can make wrong inferential statistics...
With the development and ease of access to internet networks, the potential for attacks and intrusio...
While the field of data mining has been studied extensively, most of the work has concentrated on di...
With the advent of the Internet, security has become a major concern. An intrusion detection system ...
The detection of outliers in the field of data mining (DM) and the process of knowledge discovery in...
In recent years, intrusion detection has emerged as an important technique for network security. Mac...
AbstractIn recent research, outlier mining has been widely used in areas such as telecommunication, ...
Intrusion detection is crucial in computer network security issues; therefore, this work is aimed at...
In this paper, we present a novel method for the detection of outlier in intrusion detection system....
Outlier is a data point that deviates too much from the rest of dataset. Most of real-world dataset ...
Outlier Detection is a technique to detect anomalous events or outliers during analysis of the data ...
The outlier detection in the field of data mining and Knowledge Discovering from Data (KDD) is captu...
Data mining has the vital task of Outlier detection which aims to detect an outlier from given datas...
Abstract- Outlier detection is an active area for research in data set mining community. Finding out...
The tremendous advancement and increase in usage of internet have increased the number of intruders ...
Outliers identification is essential in data analysis since it can make wrong inferential statistics...
With the development and ease of access to internet networks, the potential for attacks and intrusio...
While the field of data mining has been studied extensively, most of the work has concentrated on di...
With the advent of the Internet, security has become a major concern. An intrusion detection system ...
The detection of outliers in the field of data mining (DM) and the process of knowledge discovery in...
In recent years, intrusion detection has emerged as an important technique for network security. Mac...
AbstractIn recent research, outlier mining has been widely used in areas such as telecommunication, ...
Intrusion detection is crucial in computer network security issues; therefore, this work is aimed at...