To improve the security and privacy of audio data stored in third party servers, a novel watermarking scheme is proposed. Firstly, the authors split the host signal into frames and scramble each... Show More

To improve the security and privacy of audio data stored in third party servers, a novel watermarking scheme is proposed. Firstly, the authors split the host signal into frames and scramble each frame to get the encrypted signal. Secondly, they generate watermark bits by using the frame number and embed them into each frame of the encrypted signal, which is the data that will be uploaded to the third party servers. For the users, they can download the encrypted data and verify the data is intact or not. If the data is intact, the users decrypt the data to get the audio signal. If the audio signal is attacked in the process of transmission, they can also locate the location of the attacked frame. The experimental results show that the method proposed is effective not only for encrypted signals, but also for the encrypted signals after decryption.

Aiming at the problem that dangerous operation behaviors in the laboratory is difficult to identify by monitoring the video. An algorithm of dangerous operation behavior detection in multi-task... Show More

Aiming at the problem that dangerous operation behaviors in the laboratory is difficult to identify by monitoring the video. An algorithm of dangerous operation behavior detection in multi-task laboratory based on improved YOLOv5 structure is proposed. Firstly, the algorithm enhances, adaptively scales, and adaptively anchors box computing on the input of YOLO network. Then convolution operation is carried out to strengthen the ability of network feature fusion. Finally, the GIoU_Loss function is used at the output to optimize the network parameters and accelerate the convergence of the model. The experimental results show that the algorithm performs well in real-time head localization, head segmentation, and population regression, with significant innovation and superiority. Compared with traditional methods, this algorithm has better accuracy and real-time performance and can more effectively achieve human operation behaviors detection in laboratory application environments.