Data mining techniques, while allowing the individuals to extract hidden knowledge on one
hand, introduce a number of privacy threats on the other hand. In this paper, we study some …

In a broader sense detection of any unauthorized access of any information system is the
basic aim of any intrusion detection system. However due to cost considerations it is …

The paper presents a machine learning-based system aimed at improving the homogeneity
of tensile properties of steel strips for automotive applications over their strip length in the …

In many real word applications of neural networks and other machine learning approaches,
large experimental datasets are available, containing a huge number of variables, whose …

This paper presents an analysis of the occurrence of ripple defects during Hot Deep
Galvanising of flat steel products, with a focus on the study on thick coils having low zinc …

We live in a world of abundance of information, but lack the ability to fully benefit from it, as
succinctly described by John Naisbitt in his 1982 book,“we are drowning in information, but …

Network security is of primary concerned now days for large organizations. The intrusion
detection systems (IDS) are becoming indispensable for effective protection against attacks …

An Intrusion Detection System (IDS) with Machine Learning (ML) model Combining Hybrid
Classifiers ie Naïve Byes classifier and C 4.5 classifier is proposed for intrusion detection. In …

The main idea behind for detecting distributed denial of service attack is that the engineer
works are accessible at all the times when the Intruder attack. The user's solution for …

In the last years, the artificial neural networks have been effectively applied to several
industrial problems in order to improve knowledge and get a deeper insight into correlations …