Hybrid AI-based iBeacon Indoor Positioning Cybersecurity Attacks and Defenses Thereof

Abstract

Abstract Currently, iBeacon systems have been increasingly established in public areas to position people and assist users in indoor for location navigation. People receive the services through the Bluetooth Low Energy (BLE) installed on their mobile phones. However, the positioning and navigation functions of a iBeacon system may be compromised when faced with cyberattacks issued by hackers. In other words, its security needs to be further considered and enhanced. This study takes the iBeacon system built in Taipei Main Station, the major transportation hub with daily traffic of at least 300 thousand passengers, as an example for exploring its potential attacks and further studying on the defense technologies under the assistance of AI techniques and human participation. Our experiments demonstrate that the prior information security planning of a iBeacon system and the rolling coding encryption on its issued messages in Taipei Main Station, are the best defense methods.