Bhogeswar Borah

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Finding clusters with widely differing sizes, shapes and densities in presence of noise and outliers is a challenging job. The DBSCAN is a versatile clustering algorithm that can find clusters with differing sizes and shapes in databases containing noise and outliers. But it cannot find clusters based on difference in densities. We extend the DBSCAN(More)
The detection of outliers has gained considerable interest in data mining with the realization that outliers can be the key discovery to be made from very large databases. Outliers arise due to various reasons such as mechanical faults, changes in system behavior, fraudulent behavior, human error and instrument error. Indeed, for many applications the(More)
With the growth of networked computers and associated applications, intrusion detection has become essential to keeping networks secure. A number of intrusion detection methods have been developed for protecting computers and networks using conventional statistical methods as well as data mining methods. Data mining methods for misuse and anomaly-based(More)
Anomaly based network intrusion detection (ANID) is an important problem that has been researched within diverse research areas and various application domains. Several anomaly based network intrusion detection systems (ANIDS) can be found in the literature. Most ANIDSs employ supervised algorithms, whose performances highly depend on attack-free training(More)
Most existing network intrusion detection systems use signature-based methods which depend on labeled training data. This training data is usually expensive to produce due to cost of laboratory set up, experienced or knowledge person and non availability of ready software tool. Above all, these methods have difficulty in detecting new or unknown types of(More)
In this paper we present a clustering based classification method and apply it in network anomaly detection. A set of labeled training data consisting of normal and attack instances are divided into clusters which are represented by their representative profiles consisting of attribute-value pairs for selected subset of attributes. Each category of attack(More)
This paper describes a triangle based algorithm to transform a source image into a target image. In this paper, a digital source face image is mapped to a target face image to transform the shape of source into the target. This work is done with six steps. The initial step of the stated algorithm takes source and destination face images as input from the(More)