Mobile signaling data has the characteristics of low accuracy, large time interval and the existence of signal "ping-pong switching". In order to identify residents' travel Origin and Destination (OD) using mobile location data, a method based on Naive Bayesian Classification (NBC) was proposed. Firstly, according to the distance between places of residence and working, the travel log data measured by 80 volunteers for one month were classified statistically, and the conditional probability distribution of moving and staying states was obtained. Then, the feature parameters used to represent the user's states of moving and staying were established, including angular separation and minimum covering circle diameter. Finally, the conditional probability distribution of moving and staying states was calculated according to NBC theory, the processes with more than two consecutive moving states were clustered into travel OD. The analysis results on Xiamen mobile location data indicate that the travel time per capita obtained by proposed method has the Mean Absolute Percentage Error (MAPE) of 7.79%, which has a high precision, and the analysis results of travel OD can better reflect real travel rules.

Programmable Logic Controller (PLC) is one of the most important components of industrial control system, which controls varieties of physical equipments and production processes. The faults of PLC control program caused by malicious tempering of attacker and programming errors of internal personnel will seriously threaten equipment safety and personal safety in industrial field. In order to solve this problem, a control flow analysis method of PLC program was proposed. Firstly, the lexical and syntactic structure of source code were analyzed by using flex and bison. Then, the intermediate representation without instruction side effects was generated and optimized by analyzing the Abstract Syntax Tree (AST). Finally, the basic blocks were divided on the basis of intermediate representation, and the control flow graph of the program was constructed by taking basic block as the basic unit. The experimental results show that, the proposed method can restore the control flow structure of PLC program in the form of statement table, and provide the basis for program understanding and security analysis.

In Web service environment, the interacting entities usually cannot be predetermined and may be in different security domains. To address the access authorization for unknown users across domain borders, access control of Web service should be implemented based on domain-independent access control information but not the identities. A context-based access control policy model which can be appropriate for Web service environment was proposed. The main idea of the model was that, various access control information was abstracted and represented as a concept of context which was adopted as the center to define and perform access control policies. The context concept here acted as an intermediary between requesters and the access permissions, which was similar to the role of Role-Based Access Control (RBAC) in a way. Context-based access control policy axioms were defined based on Description Logic (DL), on the basis of these axioms, the access control policy knowledge base with the capacity of reasoning about the access control policies was put forward. Finally, the effect of access control policy enforcement was verified in Racer reasoning system, and the experiment result proved the feasibility and validity of the presented method.

With the widespread application of the data flow, the abnormal data detection problem in data flow has caused more attention. Existing Kalman filtering algorithms need small amount of historical data, but they only apply to single abnormal point detection. The effect to complex continuous outlier points is poor. In order to solve the problem, a Kalman filtering algorithm based on multidimensional impact factors was proposed. The algorithm joined the three dimensions of impact factor as space, time, provenance as well. In case of different weather and flood season, the algorithm adjusted the controlling parameters of system model parameters, and got a more accurate estimate of measurement noise. The detection accuracy of the algorithm could be improved significantly. The experimental results show that under the premise of guaranteeing similar running time, the detection error rate of this algorithm is far lower than Amnesic Kalman Filtering (AKF) and Wavelet Kalman Filtering (WKF) algorithms.

A nonlinear image encryption algorithm based on random Fractional Mellin Fransform (FrMT) was proposed to get rid of the potential insecurity problem of the linear encryption system. The random FrMT was constructed by combining log-polar transformation with random Fractional Fourier Fransform (FrFT), and a real-valued symmetrical random matrix was generated by Linear Congruential Generator (LCG) in randomizing process. The real value input image was encrypted by random FrMT which made the encryption be nonlinear, and the output ciphertext of the FrMT was also real-valued, which was convenient for storage and transmission. The encryption algorithm had three keys that were the parameters of LCG. Compared with FrMT, the fractional order key of random FrMT was more sensitive. The numerical simulation results demonstrate that the encryption algorithm is against common attacks, and sensitive to keys with good security.

Concerning the safe problem of digital image information hiding, a scrambling algorithm based on bitwise layered Arnold transform was proposed. The secret image was stratified by bit-plane, taking into account the location and pixel gray transform, each bit-plane was scrambled for different times with Arnold transforma, and the pixel was cross transposed, and adjacent pixels were bitwise XOR to get a scrambling image. The experimental results show that the secret image histogram is more evenly distributed after stratification scrambling, its similarity with the white noise is around 0.962, and the scrambling image can be restored and extracted almost lossless, which improves the robustness. Compared with other scrambling algorithms, the proposed algorithm is more robust to resist attack, and improves the spatial information hiding security.