The increasing number of network attacks causes growing problems for network operators and users. Thus, detecting anomalous traffic is of primary interest in IP networks management. In this paper we present a novel method for network anomaly detection, based on the idea of discovering Heavy Change (HC) in the distribution of the Heavy Hitters in the network traffic. To assess the validity of the proposed method, we have performed an extensive experimental evaluation phase, during which our system performance have been compared to a more classical HC-based approach. The performance analysis, presented in this paper, demonstrates the effectiveness of the proposed method
Anomaly detection of network traffic flows is a non-trivial problem in the field of network security...
We develop a behavior-based anomaly detection method that detects network anomalies by comparing the...
MasterIn recent years, network traffic anomaly detection has become an important area for both acade...
In the last years, the ever increasing number of network attacks has brought the research attention ...
The increasing number of network attacks causes growing problems for network operators and users. Th...
Abstract. We propose a novel approach for distributed statistical detection of change-points in high...
In the field of network security management, a number of recent researches have been dedicated to ne...
Abstract. Monitoring unused or dark IP addresses offers opportunities to extract useful information ...
Monitoring unused or dark IP addresses offers opportunities to extract useful information about both...
This work studies systems and methods for anomaly detection in computer networks. At first, basic ca...
In this paper, we present the design and implementation of a new approach for anomaly detection and ...
Anomaly detection in computer networks yields valuable information on events relating to the compone...
Abstract: New datamining techniques are developed for generating frequent episode rules of traffic e...
With the ever-increasing link speeds and traffic volumes of the Internet, monitoring and analyzing n...
Today’s evolving networks are experiencing a large number of different attacks ranging from system b...
Anomaly detection of network traffic flows is a non-trivial problem in the field of network security...
We develop a behavior-based anomaly detection method that detects network anomalies by comparing the...
MasterIn recent years, network traffic anomaly detection has become an important area for both acade...
In the last years, the ever increasing number of network attacks has brought the research attention ...
The increasing number of network attacks causes growing problems for network operators and users. Th...
Abstract. We propose a novel approach for distributed statistical detection of change-points in high...
In the field of network security management, a number of recent researches have been dedicated to ne...
Abstract. Monitoring unused or dark IP addresses offers opportunities to extract useful information ...
Monitoring unused or dark IP addresses offers opportunities to extract useful information about both...
This work studies systems and methods for anomaly detection in computer networks. At first, basic ca...
In this paper, we present the design and implementation of a new approach for anomaly detection and ...
Anomaly detection in computer networks yields valuable information on events relating to the compone...
Abstract: New datamining techniques are developed for generating frequent episode rules of traffic e...
With the ever-increasing link speeds and traffic volumes of the Internet, monitoring and analyzing n...
Today’s evolving networks are experiencing a large number of different attacks ranging from system b...
Anomaly detection of network traffic flows is a non-trivial problem in the field of network security...
We develop a behavior-based anomaly detection method that detects network anomalies by comparing the...
MasterIn recent years, network traffic anomaly detection has become an important area for both acade...