Security and efficiency are two key factors that affect whether a certificateless authenticated group key agreement protocol can be applied in Ad Hoc networks. To improve the security and efficiency of key management problems in securing group communications of Ad Hoc networks, a certificateless group key agreement protocol was proposed, which utilizes Elliptic Curves Cryptography (ECC) multiplication to achieve the group key agreement and authentication without pairing. Meanwhile, the Huffman key tree was used to optimize the rounds of key negotiation, decreasing the computation and communication overheads and improving the group key negotiation efficiency. Security analysis and performance comparison demonstrate that the proposed protocol has good efficiency and security in group key negotiation, which can satisfy group key establishment and rekeying for dynamic groups with restrained resources.

Android uses the permission-based access control method to protect the system resources, which has the problem of rough management. At the same time, some malicious applications can secretly access resources in a privacy scenario without the user's permission, bringing certain threats to user privacy and system resources. Based on the original permission management and control and with the introduction of Access Control List (ACL) mechanism, an Android fine-grained permission management and control system based on ACL mechanism was designed and implemented. The proposed system can dynamically set the access rights of the applications according to the user's policy, avoiding the access of malicious codes to protect system resources. Tests of compatibility and effectiveness show that the system provides a stable environment for applications.

To solve the problem of the lack of modeling and analysis of Advanced Persistent Threat (APT) attacks, an attack-defense game model based on FlipIt with asymmetric information was proposed. Firstly, the assets such as targeted hosts in the network system were abstracted as the target resource nodes and the attack-defense scenarios were described as the alternating control of the target nodes. Then, considering the asymmetry of the feedback information observed by the two sides and the incomplete defensive effect, the conditions of the payoff model and the optimal strategy of the attacker and defender were proposed in the case of renewal defense strategy. Besides, theorems of simultaneous and sequential equilibrium were proposed and demonstrated. Finally, numerical illustrations were given to analyze the factors of equilibrium strategy as well as defense payoff and to compare simultaneous and sequential equilibrium. The experimental results show that period strategy is defender's best strategy and the defender can achieve sequential equilibrium meanwhile obtaining more payoffs compared with simultaneous equilibrium by announcing her defense strategy in advance. Conclusions show that the proposed model can theoretically guide defense strategy towards stealthy APT attacks.

Feature extraction and pattern classification are two key problems in face recognition. In order to solve the high-dimensional and Small Sample Size (SSS) problem of face recognition, start with the feature extraction of human face and dimensionality reduction algorithms, a quadratic feature extraction and dimensionality reduction algorithm model was put forward based on Restricted Boltzmann Machine (RBM). At first, the image was evenly divided into a number of local image blocks and quantified, then the image was processed by Gabor wavelet transformation. The Gabor facial features were encoded by RBM to learn more intrinsic characteristics of data, so as to achieve the purpose of dimensionality reduction of high-dimensional facial features. On the basis of that, a multimodal face recognition algorithm based on Deep Belief Network (DBN) was proposed. The recognition results on ORL, UMIST and FERET face databases with different sample sizes and different resolution images show that, compared with the linear dimension reduction method and shallow network method, the proposed method achieves better learning efficiency and good recognition result.

Video background completion is attracting more and more attention. For videos captured by complexly moving camera, the problem is even more challenging. In order to solve the problem, a motion-guided optimizing algorithm was proposed to complete the spatio-temporal hole left by foreground object removal. First, to estimate the motion field in the hole, a global objective function was established, and a hierarchical iterative method was applied to find its optimal solution. Completion problem was then abstracted into a Markov Random Field (MRF) problem. Using motion field as the guidance, video background was completed by optimally assigning available pixels from other parts to the missing regions. Finally, traditional illumination transfer strategy was improved, and a new illumination adjusting method was proposed to eliminate the illumination inconsistency in the completed parts. This approach got good results on a variety of videos. Compared with previous methods, this approach works better in keeping spatio-temporal coherence, and can be applied on videos with complex background captured by complexly moving camera.

Concerning the problems of high time complexity and topological inconsistency existing in the multi-resolution representation of curve for progressive transmission, an algorithm of generating multi-resolution curves for progressive transmission over the Internet was proposed in this paper. By using pre-stored vertex deviation to simplify curves and using an optimized monotone chain intersection algorithm to maintain topological consistency, the algorithm can quickly generate topologically consistent multi-resolution curves. The algorithm was used in the experiment of progressive transmission for curve data, and the experimental results show that the multi-resolution curve data maintain topological consistency and the generation time changes linearly with the amount of data. The effectiveness of the algorithm has been verified in the experiment.