We propose a non-parametric anomaly detection algorithm for high dimensional data. We score each datapoint by its average KNN distance, and rank them accordingly. We then train limited complexity models to imitate these scores based on the max-margin learning-to-rank framework. A test-point is declared as an anomaly at α-false alarm level if the predicted score is in the α-percentile. The resul...

We propose a non-parametric anomaly detection algorithm for high dimensional data. We first rank scores derived from nearest neighbor graphs on n-point nominal training data. We then train limited complexity models to imitate these scores based on the max-margin learningto-rank framework. A test-point is declared as an anomaly at α-false alarm level if the predicted score is in the α-percentile...

This paper describes an effort to provide a holistic view of network conversation exchanges for the purpose of real-time network monitoring and anomaly detection. We argue that monitoring and anomaly detection are necessary mechanisms for ensuring secure and dependable network computing infrastructure. The model for network traffic exchange is based on a modified Ehrenfest urn model and combine...

Anomaly detection is an important aspect of data mining, where the main objective is to identify anomalous or unusual data from a given dataset. However, there is no formal categorization of application-specific anomaly detection techniques for big data and this ignites a confusion for the data miners. In this paper, we categorise anomaly detection techniques based on nearest neighbours, cluste...

In Network Security, there is a major issue to secure the public or private network from abnormal users. It is because each network is made up of users, services and computers with a specific behavior that is also called as heterogeneous system. To detect abnormal users, anomaly detection system (ADS) is used. In this paper, we present a novel and hybrid Anomaly Detection System with the uses o...

A global Internet usage enlarge rate of 380% superior than the period from 2000, the year of the dot-com bubble burst, until present select that Internet technology has become a stand of our daily life. In the similar period, cyber-crime has seen an unbelievable to facilitate to create sophisticated protection device for computers and networks a complete necessity. Firewalls as the major protec...

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...

This paper presents techniques based on relative entropy a metric for characterizing structure in data environments and applies them to both measured production performance data as well as synthetic data modeled on the statistical profiles of production data. The proposed technique provides significant improvements over industry standard Gaussian-based multivariate adaptive statistical filter (...

Existing reputation systems used by online auction houses do not address the concern of a buyer shopping for commodities—finding a good bargain. These systems do not provide information on the practices adopted by sellers to ensure profitable auctions. These practices may be legitimate, like imposing a minimum starting bid on an auction, or fraudulent, like using colluding bidders to inflate th...

An infrastructure build in the big data platform is reliable to challenge the commercial and notcommercial IT development communities of data streams in high dimensional data cluster modeling. The knowledge discovery in database (KDD) is alarmed with the development of methods and techniques for making use of data. The data size is generally growing from day to day. One of the most important st...