نتایج جستجو برای: anomaly based detection

تعداد نتایج: 3344676  

Journal: :Pattern Recognition 2010
Shehzad Khalid

Techniques for video object motion analysis, behaviour recognition and event detection are becoming increasingly important with the rapid increase in demand for and deployment of video surveillance systems. Motion trajectories provide rich spatiotemporal information about an object’s activity. This paper presents a novel technique for classification of motion activity and anomaly detection usin...

2004
Sascha Alda Armin B. Cremers

Current peer-to-peer architectures are hardly resistant against unanticipated exceptions such as the failure of single peers. This can be justified by the absence of sophisticated models for exception detection and resolution in peer-to-peer architectures. On the other hand, existing generic models for such self-adaptable architectures are rather theoretical and less suitable for the usage by e...

2011
Dennis Ippoliti Xiaobo Zhou Edward Chow Chuan Yue

Anomaly detection is a challenging problem that has been researched within a variety of application domains such as image processing, fault isolation, fraud detection, and network intrusion detection. In network intrusion detection, anomaly based techniques are particularly attractive because of their ability to identify previously unknown attacks without the need to be programmed with the spec...

2011
Senaka Buthpitiya Ying Zhang Anind K. Dey Martin L. Griss

As location-sensing smart phones and location-based services gain mainstream popularity, there is increased interest in developing techniques that can detect anomalous activities. Anomaly detection capabilities can be used in theft detection, remote elder-care monitoring systems, and many other applications. In this paper we present an ngram based model for modeling a user’s mobility patterns. ...

2011
Iñaki Garitano Roberto Uribeetxeberria Urko Zurutuza

The security of critical infrastructures is decreasing due to the apparition of new cyber threats against Supervisory Control and Data Acquisition (SCADA) systems. The evolution they have experienced; the use of standard hardware and software components or the increase of interconnected devices in order to reduce costs and improve efficiency, have contributed to this. This work reviews the rese...

2008
Gaurav Tandon Philip K. Chan Georgios C. Anagnostopoulos Debasis Mitra Marius C. Silaghi

Machine Learning for Host-based Anomaly Detection by Gaurav Tandon Dissertation Advisor: Philip K. Chan, Ph.D. Anomaly detection techniques complement signature based methods for intrusion detection. Machine learning approaches are applied to anomaly detection for automated learning and detection. Traditional host-based anomaly detectors model system call sequences to detect novel attacks. This...

Due to abundant spectral information contained in the hyperspectral images, they are suitable data for anomalous targets detection. The use of spatial features in addition to spectral ones can improve the anomaly detection performance. An anomaly detector, called nonparametric spectral-spatial detector (NSSD), is proposed in this work which utilizes the benefits of spatial features and local st...

2014
Xiurui Geng Kang Sun Luyan Ji Yongchao Zhao

Recently, high-order statistics have received more and more interest in the field of hyperspectral anomaly detection. However, most of the existing high-order statistics based anomaly detection methods require stepwise iterations since they are the direct applications of blind source separation. Moreover, these methods usually produce multiple detection maps rather than a single anomaly distrib...

2010
Jiankun Hu

Network security has become an essential component of any computer network. Despite significant advances having been made on network-based intrusion prevention and detection, ongoing attacks penetrating network-based security mechanisms have been reported. It is being realized that network-based security mechanisms such as firewalls or intrusion detection systems (IDS) are not effective in dete...

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