Abstract: As currently various portable devices were launched,
smart business conducted using them became common. Since smart
business can use company-internal resources in an exlternal remote
place, user authentication that can identify authentic users is an
important factor. Commonly used user authentication is a method of
using user ID and Password. In the user authentication using ID and
Password, the user should see and enter authentication information
him or her. In this user authentication system depending on the user’s
vision, there is the threat of password leaks through snooping in the
process which the user enters his or her authentication information.
This study designed and produced a user authentication module
using an actuator to respond to the snooping threat.
Abstract: Power System Security is a major concern in real time
operation. Conventional method of security evaluation consists of
performing continuous load flow and transient stability studies by
simulation program. This is highly time consuming and infeasible
for on-line application. Pattern Recognition (PR) is a promising
tool for on-line security evaluation. This paper proposes a Support
Vector Machine (SVM) based binary classification for static and
transient security evaluation. The proposed SVM based PR approach
is implemented on New England 39 Bus and IEEE 57 Bus systems.
The simulation results of SVM classifier is compared with the other
classifier algorithms like Method of Least Squares (MLS), Multi-
Layer Perceptron (MLP) and Linear Discriminant Analysis (LDA)
classifiers.