Affiliations: Honghe Power Supply Bureau, Yunnan Power Grid Co., Ltd., Mengzi, Yunnan 661100, China | E-mail: zhang_yuanlin@outlook.com
Correspondence:
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Corresponding author: Honghe Power Supply Bureau, Yunnan Power Grid Co., Ltd., Mengzi, Yunnan 661100, China. E-mail: zhang_yuanlin@outlook.com.
Abstract: Signal processing can complete the processing of various types of signals to obtain key data. Signal processing can also filter out redundant noise signals and ensure the quality of source signals. Due to the various functions of signal processing technology, it is widely used in network security, especially in IT asset detection and other aspects. Cyberspace is a general concept, which represents all devices associated with network connections. Detecting network assets in cyberspace means finding all networked devices. The detection of IT assets for power grid enterprises can help power grid enterprise IT administrators understand enterprise IT assets. At the same time, it can also discover the security loopholes existing in the operation of the current enterprise IT assets, and use the detection results to fix the loopholes as soon as possible to prevent the occurrence of network security incidents. This paper firstly sorts out the concepts of signal processing, cyberspace and power grid IT assets, then combines CNN and signal processing technology to design an intelligent detection strategy for power grid IT assets, and compares the designed strategy with the efficiency and other indicators of traditional detection methods. In contrast, finally, a cyberspace-based IT asset intelligent detection strategy was designed, and a power grid enterprise IT asset intelligent detection system was designed. Through the deployment strategy test environment, a test case was written in Python language, and the cyberspace-based IT asset intelligent detection was found. Compared with the traditional power grid enterprise IT asset detection scheme, the strategy has better performance in all aspects. The research adopts the method of modeling and analysis to calculate the signal values of the IT assets involved as much as possible, thereby greatly reducing the possible errors in the evaluation of enterprise IT assets. The test of the results obtained by the formula shows that the IT asset detection combined with the cyberspace search method shows superiority in different indicators.
Keywords: Signal processing, cyberspace, power grid enterprises, IT asset detection
