Rogue base stations detection for advanced metering infrastructure based on signal strength clustering

Abstract

The smart meters and meter collectors in Advanced Metering Infrastructure (AMI), which are installed in every home, rely on wireless Virtual Private Network (VPN) for communicating with Head End System (HES). Therefore, they are prone to suffer from malicious cyber-attack. Usually, based on General Packet Radio Service (GPRS) communicated method is the most popular for meter collectors and consequently they are vulnerable to rogue Base Stations (BS) and get compromised by malicious adversaries further. Thus a Density-based spatial clustering of applications with noise (DBSCAN) method is employed to filter rogue BSs out and prevent meter collectors from attaching to them, because there is a notable difference between Signal Strength (SS) profile of legitimate BSs and rogue BSs, Numerical simulation indicates that the proposed approach is capable of detecting both stationary and moving rogue BSs online within fixed time window effectively. Moreover, the method can be implemented in existing meter collectors with limited computation resource. In conclusion, the proposed approach can enhance the level of cyber security of meter collectors.