Aiming at the low efficiency of linear combination of base classifiers and over-adaptation of the traditional AdaBoost algorithm, an improved algorithm based on coefficients and diversity of base classifiers - WD AdaBoost (AdaBoost based on Weight and Double-fault measure) was proposed. Firstly, according to the error rates of the base classifiers and the distribution status of the sample weights, a new method to solve the base classifier coefficients was given to improve the combination efficiency of the base classifiers. Secondly, the double-fault measure was introduced into WD AdaBoost algorithm in the selection strategy of base classifiers for increasing the diversity among base classifiers. On five datasets of different actual application fields, compared with the traditional AdaBoost algorithm, CeffAda algorithm uses the new base classifier coefficient solution method to make the test error reduced by 1.2 percentage points on average; meanwhile, WD AdaBoost algorithm has the lower error rate compared with WLDF_Ada, AD_Ada (Adaptive to Detection AdaBoost), sk_AdaBoost and other algorithms. Experimental results show that WD AdaBoost algorithm can integrate base classifiers more efficiently, resist overfitting, and improve the classification performance.

In Synthetic Minority Over-sampling TEchnique (SMOTE), noise samples may participate in the synthesis of new samples, so it is difficult to guarantee the rationality of the new samples. Aiming at this problem, combining clustering algorithm, an improved algorithm called Clustered Synthetic Minority Over-sampling TEchnique (CSMOTE) was proposed. In the algorithm, the idea of the linear interpolation between the nearest neighbors was abandoned, and the linear interpolation between the cluster centers of minority classes and the samples of corresponding clusters was used to synthesize new samples. And the samples involved in the synthesis were screened to reduce the possibility of noise samples participating in the synthesis. On six actual datasets, CSMOTE algorithm was compared with four SMOTE’s improved algorithms and two under-sampling algorithms for many times, and CSMOTE algorithm obtained the highest AUC values on all datasets. Experimental results show that CSMOTE algorithm has higher classification performance and can effectively solve the problem of unbalanced sample distribution in the datasets.

To deal with the problem that the traditional K-means algorithm is sensitive to the initial clustering center selection, an algorithm of K-Means clustering based on Clustering degree and Distance equalization optimization ( K-MCD) was proposed. Firstly, the initial clustering center was selected based on the idea of "cluster degree". Secondly, the selection strategy of total clustering center distance equilibrium optimization was followed to obtain the final initial clustering center. Finally, the text set was vectorized, and the text cluster center and the evaluation criteria of text clustering were reselected to perform text clustering analysis according to the optimization algorithm. The analysis of simulation experiment for the text data set was carried out from the aspects of accuracy and stability. Compared with K-means algorithm, the clustering accuracy of K-MCD algorithm was improved by 18.6, 17.5, 24.3 and 24.6 percentage points respectively for four text sets; the average evolutionary algebraic variance of K-MCD algorithm was 36.99 percentage points lower than K-means algorithm. The experimental results show that K-MCD algorithm can improve text clustering accuracy with good stability.

Concerning the problem that the communication keys in transmission of mission planning system were easily stolen in White-Box Attack Context (WBAC), a new secure transmission method of mission planning system was proposed based on modified white-box Advanced Encryption Standard (white-box AES). First, the Advanced Encryption Standard (AES) was split into many lookup tables and the keys were embedded into these lookup tables, then the lookup tables were merged in accordance with the excuting order of the AES. Secondly, on the ground, different white-box AES programs were generated in accordance with the given white-box AES generation algorithms using different keys. In the end, the white-box AES programs were embedded in the security transmission of the mission planning system. When the key needed to be replaced, the original white-box AES program should be erased on the ground to generate a new white-box AES. Theoretical analysis shows that compared with the traditional secure transmission of mission planning system, the modified secure transmission method of mission planning system can make the attack complexity to 2 ⁹¹, which achieves the sufficient security and can protect the communication key.