Non-intrusive detection method of FDI attack in heating network
LIU Xin-rui
ZHANG Xiu-yu
WU Ze-qun
WANG Rui
SUN Qiu-ye
Abstract：Aiming at the problem that the heat network is susceptible to network attacks and has large inertia,in order to improve the rapidity and accuracy of heat network attack detection,this paper first proposes a non-invasive online detection method that can amplify the state deviation caused by the attack.This method first summarizes the thermal behavior of the occupants as a black box model,and the house and radiator are summarized as a white box model.The gray box model composed of white box and black box is used to calculate the indoor heat balance state.Secondly,the indoor temperature is used as the intermediate amount of input/lost heat calculation to amplify the system state deviation caused by the attack.Finally,the attack detection is carried out by the multi-matching state prediction method.In order to verify the effectiveness of the proposed method,the Bali heating network model is used for simulation experiments.Compared with the traditional detection method,the proposed method can effectively amplify the state deviation caused by the attack,and the detection speed and detection rate are higher.
Keywords：FDIcyber-attacksnon-intrusive load monitoringgray box modelheat distributing network
Publication Date：2025-07-30
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：10( 1265-1274 )