The increasing complexity of both tele and data communication networks yields new demands concerning network security. Especially the task of detecting, repulsing and preventing abuse by inand outsiders is becoming more and more difficult. This paper deals with a new technique that appears to be suitable for solving these issues, i.e. anomaly detection based on the specification of transactions...

A feature-based approach for detecting anomalies in spectral, spatial, temporal, and other domains is described. When the frequency of occurrence is small relative to the background, anomalies such as man-made objects in natural image backgrounds do not form their own clusters, but are instead assigned the nearest background cluster, becoming an outlier (statistical anomaly) in that cluster. Ou...

in order to obtain maximum information from magnetic and gravity anomaly maps, application of an edgedetection method is necessary. in this regard two commonly used methods are derivative filters and local phase filters. in this paper, a matlab code is expanded to combine an analytic signal filter and a tilt angle filter as a new edge detection filter called asta filter. this method was demonst...

mobile ad-hoc networks (manets) by contrast of other networks have more vulnerability because of having nature properties such as dynamic topology and no infrastructure. therefore, a considerable challenge for these networks, is a method expansion that to be able to specify anomalies with high accuracy at network dynamic topology alternation. in this paper, two methods proposed for dynamic anom...

as networking and communication technology becomes more widespread, thequantity and impact of system attackers have been increased rapidly. themethodology of intrusion detection (ids) is generally classified into two broadcategories according to the detection approaches: misuse detection and anomalydetection. in misuse detection approach, abnormal system behavior is defined atfirst, and then an...

Anomaly detection in big data is a key problem in the big data analytics domain. In this paper, the definitions of anomaly detection and big data were presented. Due to the sampling and storage burden and the inadequacy of privacy protection of anomaly detection based on uncompressed data, compressive sensing theory was introduced and used in the anomaly detection algorithm. The anomaly detecti...

rise in temperature occurred after soil temperature was measured in different time series. in this article, ldf (logarithmic derivative filter) innovative method is applied to detect anomalies. this method tests soil temperature time series for 12 earthquakes in iran with magnitudes of either five or greater than five. results from this method were collected. based on the results of ldf method ...

Anomaly Detection of Web-based Attacks. Christopher Kruegel chriscs.ucsb.edu. Giovanni Vigna vignacs.ucsb.edu. University of.Using Generalization and Characterization Techniques in the. Anomaly-based Detection of Web Attacks. William Robertson, Giovanni Vigna, Christopher.tem that detects web-based attacks using a number of different techniques. The anomaly detection system takes as input web s...