Anomaly Detection (AD) has recently become an important application of hyperspectral images analysis. The goal of these algorithms is to find the objects in the image scene which are anomalous in comparison to their surrounding background. One way to improve the performance and runtime of these algorithms is to use Dimensionality Reduction (DR) techniques. This paper evaluates the effect of thr...

This paper presents some proposals and contributions in network-based intrusion-related technologies. Two key points are discussed in this line: anomaly-based intrusion detection, and active response mechanisms. The first issue is mainly focused on the consideration of a stochastic approach to model the normal behavior of the network system to be monitored and protected. This anomaly-based dete...

Ranking measure is of prime importance in anomaly detection tasks because it is required to rank the instances from the most anomalous to the most normal. This paper investigates the underlying assumptions and definitions used for ranking in existing anomaly detection methods; and it has three aims: First, we show evidence that the two commonly used ranking measures—distance and density—cannot ...

Data mining is an interdisciplinary subfield of computer science involving methods at the intersection of artificial intelligence, machine learning and statistics. One of the data mining tasks is anomaly detection which is the analysis of large quantities of data to identify items, events or observations which do not conform to an expected pattern. Anomaly detection is applicable in a variety o...

Résumé. Intrusion detection is an important topic dealing with security of information systems. Most successful Intrusion Detection Systems (IDS) rely on signature detection and need to update their signature as fast as new attacks are emerging. On the other hand, anomaly detection may be utilized for this purpose, but it suffers from a high number of false alarms. Actually, any behaviour which...

The wide spread of worms poses serious challenges to today’s Internet. Various IDSes (Intrusion Detection Systems) have been proposed to identify or prevent such spread. These IDSes can be largely classified as signature-based or anomaly-based ones depending on what type of knowledge the system knows. Signature-based IDSes are unable to detect the outbreak of new and unidentified worms when the...

In 1987 Dorothy Denning wrote in her seminal paper “An Intrusion-Detection Model” the following words: “exploitation of a system’s vulnerabilities involves abnormal use of the system; therefore, security violations could be detected from abnormal patterns of usage.” With these words, Denning kicked off 20 years of research, development, and publications in anomaly-based intrusion detection, whe...

Web site defacement, the process of introducing unauthorized modifications to a web site, is a very common form of attack. Detecting such events automatically is very difficult because web pages are highly dynamic and their degree of dynamism, as well as their typical content and appearance, may vary widely across different pages. Anomaly based detection can be a feasible and effective solution...

increasing the popularity of sip based services (voip, iptv, ims infrastructure) lead to concerns about its ‎security. the main signaling protocol of next generation networks and voip systems is session initiation protocol ‎‎(sip). inherent vulnerabilities of sip, misconfiguration of its related components and also its implementation ‎deficiencies cause some security concerns in sip based infra...

Anomaly detection is a popular problem in many fields. We investigate an anomaly detection method based on probability density function (PDF) of different status. The constructed PDF only require few training data based on Kullback–Leibler Divergence method and small signal assumption. The measurement matrix was deduced according to principal component analysis (PCA). And the statistical detect...