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 that some area deforms too large and large volume of redundant data in the process of panoramic video mapping, a Double-Ring mapping Projection (DRP) algorithm was proposed. Firstly, according to the geometric characteristics of spherical video and the visual characteristics of Human Visual System (HVS), the spherical video was divided into 14 equal-sized regions by two mutually orthogonal ring areas regions. Then, according to the space domain sampling theorem, the 14 regions corresponding to the spherical video content were mapped to 14 rectangular videos with the same size by Lanczos interpolation method. Finally, according to the characteristics of the latest video coding standard, the 14 rectangular videos were rearranged to get a compact panoramic video in keeping with coding standards. The experimental results show that the DRP algorithm achieve a higher compression efficiency compared with the EquiRectangular mapping Projection (ERP) algorithm, OctaHedral mapping Projection (OHP) algorithm and IcoSahedral mapping Projection (ISP) algorithm. Specifically, compared with the most popular ERP algorithm, the proposed method reduces the bit rate by 8.61% which obviously improves the coding efficiency.

Video transcoding is applied in the field of Internet video coding. When the original video is transcoded multiple times, only the distortion between the input video and the output video can be calculated and the distortion between the output video and the original video can not be learned. Here an algorithm for estimating the distortion between the output video and the original video was proposed to control the quality of the output program. Firstly, the superposition of distortion caused by multiple lossy transcoding was analyzed to derive the lower limit of total distortion. Then the probability method was exploited to make an estimation on the distortion between the original video and the final output video. Finally, the least square fitting was used to correct the estimation according to the prediction error. Experimental results demonstrate that the proposed algorithm can accurately estimate the distortion with the prediction error of 0.02dB, 0.05dB and 0.06dB for Y, U and V components on average respectively after correction.

At present, the parameters of high sulfur gas purification process present timing autocorrelation characteristics, resulting in poor static multivariate statistical process monitoring for abnormal condition. An anomaly detection and diagnosis method called Dynamic Kernel Independent Component Analysis (DKICA) was proposed, which considered the timing autocorrelation of parameters. Firstly, Auto-Regression (AR) model was introduced. The model order was determined by the parameter identification to describe the timing of autocorrelation in the monitoring process. Secondly, original variables were projected to a kernel independent space, their T ² and SPE statistics were monitored to realize anomaly detection by judging whether they exceeded control limit of normal condition. Finally, the first order partial derivative of the T ² statistic to original variable was calculated, and the contribution plot was given to achieve abnormality diagnosis. The data collected from a high sulfur gas purification plant was analyzed, and the results showed the detection accuracy of DKICA was prior to that of Kernel Independent Component Analysis (KICA).

To deal with the lung segmentation problem under complex conditions, Random Walk algorithm was applied to automatic lung segmentation. Firstly, according to the anatomical and imaging characteristics of the chest Computed Tomography (CT) images, foreground and background seeds were selected respectively. Then, CT image was segmented roughly by using the Random Walk algorithm and the approximate mask of lung area was extracted. Next, through implementing mathematical morphology operations to the mask, foreground and background seeds were further adjusted to adapt to the actually complicated situations. Finally, the fine segmentation of lung parenchyma for chest CT image was implemented by using the Random Walk algorithm again. The experimental results demonstrate that, compared with the gold standard, the Mean Absolute Distance (MAD) is 0.44±0.13 mm, the Dice Coefficient (DC) is 99.21%±0.38%. Compared with the other lung segmentation methods, the proposed method are significantly improved in accuracy of segmentation. The experimental results show that the proposed method can solve the difficult cases of the lung segmentation, and ensure the integrity, accuracy, real-time and robustness of the segmentation. Meanwhile, the results and time of the proposed method can meet the clinical needs.

According to the difference between normal users visiting patterns and abnormal ones, a new method to detect applicationlayer Distributed Denial of Service (DDoS) attack was proposed based on IP Service Request Entropy (SRE) time series. By approximating the Adaptive AutoRegressive (AAR) model, the SRE time series was transformed into a multidimensional vector series regarded as a description of current users visiting patterns. Furthermore, a Support Vector Machine (SVM) classifier was applied to classify vector series and identify the attacks. The simulation results show that this approach not only can distinguish between normal traffic and DDoS attack traffic, but also is suitable to detect DDoS attack against the large scale network traffic, which does not arouse the sharp changes of the network traffic.

Palm-dorsal vein recognition using Uniform Discrete Curvelet Transform （UDCT） was proposed in this paper. With the palm-dorsal Region Of Interest (ROI) extraction and image preprocessing, UDCT of the curvelet Transform was used on ROI. Then, the curvelet coefficients phase variance was encoded. Finally, the Chi-square distance of histogram of the coding was used for vein recognition. The experimental results show that this proposed method can identify palm-dorsal vein images with high robustness and high speed even with poor-quality images.

Defending against distributed denial of service attacks is one of the hardest security problems on the Internet today.Among several countermeasures,adaptive probabilistic packet making(APPM) is promising.Every router marks a passing packet with a probability that is adaptive to a given strategy,so that a minimum convergence time for an attacking path can be achieved to the victim,and the victim can be found in attack path reconstruction using IP traceback method.In this paper,an adaptive probabilistic packet making scheme was given.Compared to common schemes,it reduced the number of packets needed for path reconstruction,and the computation overhead and false proofs in path reconstruction were effectively reduced.

The efficiency of the interception affects directly on the result of the soccer match in Robot World Cup. Base on the model of the intercepting soccer, the equation is deduced, then the position of the interception can be calculated with the root of the equation. Obtaining the root of the equation is the critical of improving the efficiency. Effective chord secant method(CSM) was used to determine the root of the quation quickly. Experiments results show that the efficiency of CSM is influenced greatly by the variation of the quation. The shape of the curves affects directly the speed of the convergence of CSM. In order to improve the convergence of CSM, an optimization is needed. Compared with the CSM before optimizing and dichotomy, the result has shown that the integrative effectiveness of the new method is much better. This new method also satisfies the need of the interception speed required in Robot World Cup.