Focused on the disadvantages of slow convergence and easy to fall into local optimum of Harris Hawks Optimization （HHO） algorithm， an improved HHO algorithm called Chemotaxis Correction HHO （CC-HHO） algorithm was proposed. Firstly， the state of convergence curve was identified by calculating the rate of decline and change weight of the optimal solution. Secondly， the CC mechanism of the Bacterial Foraging Optimization （BFO） algorithm was introduced into the local search stage to improve the accuracy of optimization. Thirdly， the law of energy consumption was integrated into the updating process of the escape energy factor and the jump distance to balance the exploration and exploitation. Fourthly， elite selection for different combinations of optimal solution and sub-optimal solution was used to improve the universality of global search of the algorithm. Finally， when the search was falling into local optimum， the escape energy was disturbed to realize the forced jumping out. The performance of the improved algorithm was tested by ten benchmark functions. The results show that the search accuracy of CC-HHO algorithm on unimodal functions is better than those of Gravitational Search Algorithm （GSA）， Particle Swarm Optimization （PSO） algorithm， Whale Optimization Algorithm （WOA） and other four improved HHO algorithms for more than ten orders of magnitude； there is also more than one order of magnitude superiority on multimodal functions； on the premise that search stability is improved by more than 10% on average， the proposed algorithm has faster convergence speed significantly than the above-mentioned several comparative optimization algorithms with more obvious convergence trend. Experimental results show that CC-HHO algorithm effectively improves the efficiency and robustness of the original algorithm.

To minimize damage from network security problem, an improved network security situation assessment model based on Fuzzy Analytic Hierarchy Process (FAHP) was proposed. First, a set of index system in conformity with actual environment which consists of index layer, criterion layer and decision layer was established in consideration of the large-scale network environment in the future. Aiming at the influence on evaluation by data distribution uncertainty and fuzziness in situation assessment, the proposed model used Fuzzy C-Means (FCM) clustering algorithm and the best clustering criterion for data preprocessing to get the optimal cluster number and cluster center. Finally, multi-factor secondary assessment model was established for situation assessment vector. The simulation results show that, compared with the present situation assessment method based on FAHP, the improved method takes the factors which have small weights into consideration better, so the standard deviation is smaller and evaluation results are more objective and accurate.

Constant improvement of botnet structure has caused great threat to network security, so it is very important to study the inherent characteristics of botnet structure to defense this kind of attack. This paper simulated the unstructured P2P botnet from the perspective of complex network, then proposed metrics and applied the theory of complex centrality to analyze the robustness of the unstructured P2P botnet when it encountered nodes failure. The experimental results demonstrate that the unstructured P2P botnet displays high robustness when it encounters random nodes failure, but its robustness drops quickly when it encounters central nodes failure.

In order to treat the problem of routing security in wireless sensor network, data fusion event was both spatially and temporally correlated. Low Energy Adaptive Clustering Hierarchy (LEACH) was improved and nodes' behavior trust was taken into account, a secure data fusion and routing algorithm based on behavior trust (BTSR) was proposed. The security and reliability of the algorithm were implemented by using statistical hypothesis test for matching the reading sequence of sensors and statistical characters of the data fusion event. The simulation results show that BTSR is better than LEACH on security probability, energy consumption and fusion precision.