AES Encryption Simulation for Improving Multi-Sensor Information of Autonomous Service Robots
Currently,information may be tampered with or cracked during transmission.Therefore,a multi-sensor information encryption method for autonomous service robots was proposed.Firstly,the Jaccard coefficient and relative matching degree were employed to measure the similarity of sensor information between autonomous service robots,thus cleaning up the duplicate information.Meanwhile,Mahalanobis distance was used to filter out abnormal sensor information.Subsequently,the RBF neural network was applied to fuse the preprocessed multi-sensor information.Moreover,the AES encryption algorithm and Henon mapping were improved separately and combined.Finally,a joint encryption algorithm was used to encrypt multi-sensor information for autonomous service robots.Simulation results demonstrate that after encryption,the information entropy of character data is closer to 8,and the pixel change rate of image information is higher.Meanwhile,the encryption and decryption time is shortened.All the above fully verifies the information encryption effect of the proposed method.
Autonomous service robotMulti-sensor informationInformation fusionAES encryption algorithmHenon mapping
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