Object tracking based on Siamese network has made some progresses, that is it overcomes the limitation of the spatial invariance of Siamese network in the deep network. However, there are still factors such as appearance changes, scale changes, and occlusions that affect tracking performance. Focusing on the problems of large changes in object scale, object motion blur and small scale of object in the specified object tracking of Unmanned Aerial Vehicles (UAV), a new tracking algorithm was proposed based on the Siamese region proposal attention mechanism network, namely Attention-SiamRPN+. Firstly, an improved deep residual network ResNet-50 was employed as a feature extractor to extract feature maps. Secondly, the channel attention mechanism module was used to filter the semantic information of different channel feature maps extracted by the residual network, and the corresponding weights to different channel features were reassigned. Thirdly, a hierarchical fusion of two Region Proposal Networks (RPN) was applied. The RPN module was consisted of channel-by-channel deep cross-correlation of feature maps, classification of positive and negative samples and bounding box regression. Finally, the box of the object position was selected. In the test on the VOT2018 platform, the proposed algorithm had the accuracy of 59.4% and the Expected Average Overlap (EAO) of 39.5%. In the experiment with one-pass evaluation mode on the OTB2015 platform, the algorithm had the success rate and precision of 68.7% and 89.4% respectively. Experimental results show that the evaluation results of the proposed algorithm are better than the results of three excellent correlation filtering tracking and Siamese network tracking algorithms in recent years, and the proposed algorithm has good robustness and real-time processing speed when applying to the tracking of specified objects of UAV.

Aiming at the problem of personal privacy protection in Internet car rental scenario, a personal privacy protection mechanism based on blockchain was proposed. Firstly, a framework for personal privacy protection based on blockchain was proposed for solving personal privacy issues exposed in the Internet car rental. Secondly, the design and definition of the model were given by participant profile, database design and performance analysis, and the framework and implementation of the model were expounded from the aspects of granting authority, writing data, reading data and revoking authority. Finally, the realizability of the mechanism was proved by the system development based on blockchain.

Feature fusion has become a heated research topic in steganalysis. In order to solve the problems in the existing feature fusion methods, such as feature dimension disaster in serial feature fusion method and only two kinds of features can be integrated in parallel feature fusion method, this paper proposed a JPEG steganalysis approach based on parallel feature fusion by quaternion. The method firstly selected the four fusion features, and then isolated redundant components by the Principal Component Analysis (PCA), finally combined four features as quaternion vector to achieve multi-feature parallel fusion using the four components of the quaternion. The experimental results show that, compared with the traditional feature fusion method, the proposed method effectively improves the detection rate of steganalysis in JPEG images, and has better robustness.