Unmanned aerial vehicle anomaly detection method based on multi-log collaborative analysis

Abstract

An unmanned aerial vehicle anomaly detection method based on multi-log collaborative analysis comprises the following steps: conducting template extraction in an unmanned aerial vehicle flight log, extracting features of different events, and expressing text information of the unmanned aerial vehicle flight log in the form of feature vectors; carrying out dimension reduction operation on the obtained feature vectors by utilizing a PCA algorithm; classifying events into a known cluster according to the shortest Euclidean metric by using a k-medoids algorithm; identifying the events, carrying out anomaly detection on the events, judging whether the events are abnormal events or not, if not, putting the events back to the training data set for training in the learning stage, and if yes, continuing to judge whether the attack model is known or not, and if not, defining the abnormal events as a new attack model, and if so, classifying the abnormal events as a known attack model. According to the method, the speed and accuracy of module extraction and the accuracy of exception detection can be improved, and finally the attack model of the abnormal events is given.

Description

technical field [0001] The invention belongs to the field of unmanned aerial vehicle anomaly detection, and relates to an unmanned aerial vehicle anomaly detection method based on multi-log collaborative analysis. Background technique [0002] UAVs are unmanned aircraft operated by radio remote control equipment and self-contained program control devices. Compared with manned aircraft, they have more advantages and can be used for tasks that are too "dull, dirty or dangerous". UAVs can be divided into military and civilian applications according to their application fields. In terms of military use, UAVs include reconnaissance aircraft and target aircraft. In terms of civilian use, the combination of drones and industrial applications is the real rigid demand for drones. At present, the application in the fields of aerial photography, agriculture, plant protection, express transportation, disaster rescue, observation of wild animals, monitoring of infectious diseases, surv...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a UAV anomaly detection method based on multi-log collaborative analysis, which can improve the efficiency of module extraction. Speed, accuracy, and accuracy of anomaly detection, and finally an attack model for anomalous events

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