SECURITY APPRAISAL CONDUCTED ON REAL TIME SCADA DATA SET USING CYBER ANALYTIC TOOLS

Authors

  • K.SANGEETHA , S.VENKATESAN ,S. SHITHARTH

Abstract

In this contemporary cyber world, grid systems play a crucial role. In those grids, security aspect
is always prime. Supervisory Control and Data Acquisition (SCADA) is the centralized system that control
the entire grid. When a system is considered to be a whole and sole control of huge grid then obviously an
uncompromised security would be the vital. By having that as a major concern a lot of research is being
done on IDS security. In spite of that it has several cons including increased fake positive and fake negative
rates, which will invariably leads to a larger chaos. This research work is actually a prework to implement
machine learning algorithms in the SCADA data set to segregate testing and training data and to further
optimize. So a real time SCADA data set collected from the test bed is tested with two major tools netstat
and snort. These tools helps in analysing the entire network traffic and it also helps in finding any anomaly /
outliers present inside the network. This research work helps in scrutinizing the network data by finding out
the intruders not just stopping by that but also add the attack in the library database for future use.

Published

2020-01-31

Issue

Section

Articles