Insider Attack Detection in IoT devices using Data Analytics

In the recent years, the rate of theft of money being carried to ATM machines is increasing day by day. Each vehicle carrying money should be monitored at all times through communication protocol and the vehicle should have a GPS installed. This location information should be very confidential and accessible only to the authorized officials. Due to the advancement in the technology, there are numerous ways in which the attacks are happening. One such attack is accessing the confidential information (i.e., the GPS location of the vehicle in this case) by unauthorized means from the people within the same network and using it for various purposes. It's become a challenge to overcome these attacks and deposit the amount to ATM machines safely. There are other scenarios viz. carrying the witnesses to the court, shipping important materials like medicines or official documents where the GPS information is being misused. Providing security against insider attacks is the need of the hour. This paper mainly focuses on the development of an end-to-end system which detects the unauthorized access to the confidential information and gives analysis of the time and frequency of attack using data analytics.