A Power IoT Terminal Asset Identification Technology Suitable for Modbus Protocol

In the new power system scenario, Power IoT terminals have new characteristics such as diverse hardware heterogeneity and complex subject ownership, which make it technically difficult to achieve secure access authentication based on traditional terminal hardware fingerprint recognition technology. A power IoT terminal fingerprint recognition technology suitable for the Modbus protocol is proposed to solve this problem. This method combines the characteristics of Modbus protocol packet parsing, which is a common industrial control communication protocol. Firstly, based on active packet detection technology, it realizes the survival judgment of business terminals and constructs a coarse-grained topology image of terminal production. Then, by passively monitoring and analyzing the characteristics of terminal interaction traffic behavior, a terminal behavior fingerprint recognition model is constructed based on the deep learning algorithm BiLSTM to achieve accurate terminal type discrimination, thereby establishing a power IoT terminal fingerprint recognition model. The experimental results in a distributed photovoltaic scenario show that the method has an average classification and recognition accuracy of 89.6% for common power business terminals, which can basically meet the lightweight and non-invasive business requirements of terminal fingerprint recognition in new power system scenarios.