In order to solve the Knapsack Problem with a single Continuous variable (KPC) efficiently, a novel S-shape transfer function based on Gauss error function was proposed, and a new approach of transforming a real vector into a 0-1 vector by using the proposed transfer function was given, thereby a New Binary Particle Swarm Optimization algorithm (NBPSO) was proposed. Then, based on the second mathematical model of KPC and the combination of NBPSO and the effective algorithm to deal with the infeasible solutions of KPC, a new approach to solve KPC was proposed. For validating the performance of NBPSO in solving KPS, NBPSO was utilized to solve four kinds of large-scale KPC instances, and the obtained calculation results were compared with those of Binary Particle Swarm Optimization algorithms (BPSOs) based on other S and V-shape transfer functions, Single-population Binary Differential Evolution with Hybrid encoding (S-HBDE), Bi-population Binary Differential Evolution with Hybrid encoding (B-HBDE) and Binary Particle Swarm Optimization algorithm (BPSO). The comparison results show that NBPSO is superior to the comparison algorithms in average calculation result and stability, illustrating that NBPSO has the performance better than other algorithms.

With the rapid development of the Internet of Things (IoT), the research and application of Low-power and Lossy Network (LLN) has become a trend of development. Firstly, the basic principle and structure of IPv6 over Low-power Wireless Personal Area Network (6LoWPAN) and Routing Protocol for Low-power and lossy network (RPL) were introduced. Secondly, the main security threats of RPL routing in LLN and the corresponding solutions were summarized, classified and compared through the different strategies adopted by the protocol. Then, the research status of existing secure RPL at home and abroad was introduced and analyzed. At the same time, the existing security threats and solutions were summarized. Finally, the security issues and development trends that needed to be further studied in large-scale, mobile, self-organizing and low-power RPL were proposed.

The null models of complex networks generated by random scrambling algorithm often can't tell when null models can be stable because of the difference of successful scrambling probabilities of different order null models. Focusing on the issue, the concept of "successful scrambling times" was defined and used to replace the usual "try scrambling times" to set the algorithm. The index of the proposed successful scrambling times could be added only when the randomly selected edges could meet the scrambling conditions of corresponding null models, and thus be successfully scrambled. The generation experiments of null models of every order show that every index can be stable in a small scale of successful scrambling times. Further quantitative analyses show that, according to the corresponding orders, 0-order, 1-order and 2-order null models with good quality can be got by setting successfully scrambling times to be 2 times, 1 times and 1 times of actual networks' edge number respectively.

Concerning of the low accurate rate of active defense technology, a heuristic detection system of Trojan based on the analysis of trajectory was proposed. Two kinds of typical Trojan trajectories were presented, and by using the behavioral data on Trojan trajectory the danger level of the suspicious file was detected with the decision rules and algorithm. The experimental results show that the performance of detecting unknown Trojan of this system is better than that of the traditional method, and some special Trojans can also be detected.

The near-surface defects are hard to identify in ultrasonic phased array Non-Destructive Testing (NDT), thus a new intelligent identification method based on fractal theory was proposed to solve this problem. A box-counting dimension algorithm based on linear interpolation was described to calculate the box-counting dimension of 140 groups of ultrasonic A-Scan time domain signals. Then the distribution of box-counting dimension was analyzed using the statistical method. The experimental results show that ultrasonic A-Scan signal is obviously fractal and it is effective to analyze the A-Scan signal with the fractal approach. This method has the potential to identify near-surface defects since the values of the box counting dimension of defective signals are different from those of defective signals. As a result, the detection rate of near-surface defects can be improved and the omission rate caused by man-made factors can be reduced in ultrasonic phased array automatic testing.

The current disadvantages of Mobile Ad Hoc Network (MANET) test method include simple model, high cost and difficult duplicate. In this paper, a large-scale MANET hybrid emulation testing method based on NS2 (LHEN) was proposed to solve these problems. By making use of simulation function of NS2, the authors could complete encapsulation and decapsulation of real packets and virtual packets with Tap agent, thus they could achieve the communication between virtual environment and real environment through network objects and NS2 real-time scheduler. A real node movement could be emulated by controlling network wireless signal strength, and then a real network environment was established. Finally, the authors constructed a large scale MANET respectively for contrast experiments through method of hybrid emulation and simulation. The experimental results show that the performance is almost consistent and mean difference value is lower than 18.7%, which means LHEN is able to be applied in some indicators test and verification for a large scale MANET.

A new localization algorithm based on reputation mechanism was proposed to improve the robustness of the node positioning system in Wireless Sensor Network (WSN). This algorithm introduced a monitoring mechanism and reputation model to filter out malicious beacon nodes giving the false location information, used Beta distribution to update and integrate the reputation of the beacon nodes. Through the cluster head node, the proposed algorithm collected and judged which beacon nodes were reliable, increased the malicious beacon nodes detection rates while the positioning error was reduced. Finally, the simulation and detailed analysis prove its efficiency and robustness. The algorithm is efficient in self-positioning of sensor nodes in distributed WSN, and the localization accuracy and security are greatly improved.

Based on a thorough research on the time-domain security of BLP(Bell-LaPadula) model,an incorrect understanding on the time-domain security of BLP model was pointed out,and a new theoretical proof about the time-domain security of BLP model was given.The BLP model accords well with the requirement of confidentiality was indicated.