With the rapid development of Internet of Things （IoT） and industrial Internet， the research of cyberspace security has been paid more and more attention by industry and academia. Because the source code cannot be obtained， binary code similarity search has become a key core technology for vulnerability mining and malware code analysis. Firstly， the basic concepts of binary code similarity search and the framework of binary code similarity search system were introduced. Secondly， the development status of binary code technology about syntax similarity search， semantic similarity search and pragmatic similarity search were discussed. Then， the existing solutions were summarized and compared from the perspectives of binary hash， instruction sequence， graph structure， basic block semantics， feature learning， debugging information recovery and advanced semantic recognition of functions. Finally， the future development direction and prospect of binary code similarity search were looked forward to.

Network management becomes more difficult for the increase of data transmission speed and network complexity, so the paper presented an intelligent multi-Agent model for virtual resource, described the process of the multi-Agent to virtual resource, and discussed the processing mechanism of different Agent. The proposed model was able to analyze social media resources in real-time by user context and system state. It automatically allocated resources suitable for users according to the virtual resource usage type and the information demand analysis of user context. The model was evaluated by dynamic scheduling method of virtual resources in cloud computing and the MovieLens system. The results show that the proposed model has better performance, can achieve the dynamic scheduling and load balancing of virtual resource, so that users can utilize efficiently virtual resource in the cloud computing.

Taking into account the relatively poor versatility and effectiveness of the general robot visual navigation filtering algorithm, and taking advantage of the existing the median filter and multi-scale adaptive fusion filter, a combinatorial optimization filter based on the median and multi-scale was proposed. Firstly, the algorithm uses the median filter, and then uses the multi-scale filter. Finally the filtered results are fused according to smallest mean absolute error criterion(MAE). Experimental results show that the proposed algorithm can better filter out a variety of common noise for the robot road images, which enhances the versatility and effectiveness of the algorithm.

Center extraction is a primary stage in the extraction of Placido image. Therefore, a curve fitting method is proposed to detect the center. Firstly, Hough transform was used to locate the approximate center, and Placido image was located in the polar coordinate. Then the Gaussian kernel function was convolved with the image, and the points were detected in the polaraxis. Finally, based on the coordinates of these points, the accurate center was obtained by the ellipse fitting method. The precision can be brought to the order of sub-pixels by this algorithm and the mean error of diopter is less than 0.25D. Extracting results show that proposed method has higher accuracy and better robustness and provides guarantee on the precise corneal topography.

The application of particle filtering in real video-based multi-target tracking systems is limited because of its high computational complexity. To overcome the efficiency bottleneck, a coarse-grained parallel multi-target tracking implementation based on the OpenMP-specified shared-memory parallel programming model was explored. A list of tracked targets was maintained in a shared variable, and each target was tracked by an independent particle filter. The number of threads and the number of targets tracked by each thread were determined by the number of processing units. Compared to its corresponding optimized sequential version, the parallel implementation, which increases the number of targets in real-time tracking from 2 to 8, is of much more practical value.