Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2022-05-18 Cooperative journals: 《计算机应用研究》
Abstract： In order to resist the attack of quantum algorithm and deal with the defect that malicious signers can output multiple signatures using the complete anonymity of ring signature technology to carry out double overhead attack, and to solve the unnecessary waste of system overhead, this paper proposed a new identity-based linkable ring signature scheme form lattice. The scheme takes the approximate shortest vector problem on the lattice as the security basis, reduces the solution of the problem to the solution of the collision problem, generates the signature by using the linear operation between matrix vectors, and combines the identity-based cryptography technology. It solved the problem of system overhead waste, does not involve complex algorithms such as trapdoor generation and Gaussian sampling, improves the signature efficiency and reduces the storage overhead. It is verified that the scheme meets the requirements of complete anonymity and strong unforgeability under the random oracle model. After analysis, the scheme is a secure and efficient ring signature scheme.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2022-04-07 Cooperative journals: 《计算机应用研究》
Abstract： The slater voting rule is a tournament-based voting rule. It mainly constructs a ringless tournament, finds the one with the smallest difference from the original tournament, and selects the winner from it. Aiming at the NP-hard slater voting algorithm, this paper proposed a picat method to solve the slater problem based on the optimization of similar candidate item sets. Compared with the non-optimized picat method for solving the slater problem, this method reduces the solution space of the slater algorithm, effectively reduces the amount of calculation for solving the slater winner, and improves the calculation speed. The experimental results show that the computational speed of the optimized picat method for solving the slater problem is better than that of the non-optimized; when the number of candidates is less than 20, the computational speed and computing power of the answer set program (ASP) method for solving the slater problem are better than those of the optimized picat method, but when the number of candidates exceeds 30, the optimized picat method (with a satisfiable problem solver) outperforms the ASP method in terms of computational speed and computational power.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-04-01 Cooperative journals: 《计算机应用研究》
Abstract： Generative adversarial networks (GAN) is one of the most popular generation models of the year. Using the generation antagonistic network and some of its improved models, the model can generate random images, or specific images of low quality. At present, there is no generation model that can use simple network structure to generate high-quality specific images. For this task, the method combines the advantages of boundary equilibrium generative adversarial network(BEGAN) , adds additional condition features and the MSE loss and establishes the conditional boundary equilibrium generative adversarial network(C-BEGAN) . This method used to extract the generation model for specific image generation. Experimental results show that compared with other supervised class generation models, this method can use simpler networks to achieve faster convergence speed and generate images with better quality and diversity.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-04-01 Cooperative journals: 《计算机应用研究》
Abstract： Aiming at the quantification of data privacy and data utility in privacy protection, based on the basic principles of metric space and norm, this paper proposed a privacy and data utility metric model. First, it gave the data numerical processing method. The data was converted into a matrix for calculation. Secondly, it introduced a privacy preference function to measure the change of sensitive attributes over time. Then, it analyzed the privacy protection model and quantified the data changes generated by the privacy protection technology. Finally, this paper built a metric space, and gave privacy amount, data utility and privacy protection calculations. Simulation experiments show that the established metric model can effectively reflect the amount of private information.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-12-13 Cooperative journals: 《计算机应用研究》
Abstract： Based on the automatic search algorithm to solve differential characteristic and linear characteristic, it has become hot topics in differential attack and linear attack. This paper presented a differential characteristic and linear characteristic method based on the half-byte MILP model for automatic search cryptanalysis. This method is used to analyze for the LED lightweight block cipher, to solve the number of active S-boxes with fewer variables and constraint inequalities. The 4 rounds of LED obtained at least 25 active S-boxes, which is same as theoretical value given by the LED designer, verifying the correctness of the half-byte MILP model. Finally, this paper calculated the maximum differential characteristic probability and the maximum linear characteristic probability of LED, which proves that it can resist differential attack and linear attack.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-12-13 Cooperative journals: 《计算机应用研究》
Abstract： In order to solve the user experience reduction by bandwidth jitter that caused video frame loss during live video, This paper proposed a real-time prediction model (VBRP) of H. 265 video bandwidth. The model is based on markov chain and focuses on the live video stream encoded by H. 265. It studied the statistical characteristics of frame B in the GOP(Group of pictures) encoding mode, which showed that the B frames size had a great influence on the transmission rate of video stream and used this feature, it can predict the size of the B frame, then according to the network bandwidth selective discarding the B frame, at the same time used the number of frames adjustment factor AF and error threshold FT, to balance the training frequency and the number of predicted frames when predicting B frames. Finally, the prediction algorithm is implemented and validated in the live video system.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-10-11 Cooperative journals: 《计算机应用研究》
Abstract： There is a serious overestimation problem in deep Q net, which leads to reduce the ability of the agent to find the optimal strategy. In order to relieve the overestimation in deep Q net, this paper proposed a correction function to improve the evaluation function of Deep Q Net. when the selected action is the optimal action, the correction function is 1, and the current state-action value is not modified. When the selected action is not the optimal action, the correction function is less than 1, and the current state-action value is reduced. Thus the difference between non-optimal state-action values increases, reducing the impact of overestimation. Experiments show that the improved algorithm achieves better performance in Playing Atari 2600 and OpenAI Gym. indicating that the improved algorithm could find a better strategy than deep Q net.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-10-11 Cooperative journals: 《计算机应用研究》
Abstract： The traditional Naive Bayes classification algorithm does not divide the importance degree according to the different feature items, which makes the classification result inaccurate. In order to solve this problem, this paper introduces Jensen-Shannon (JS) divergence and uses JS divergence to express the amount of information provided by the feature terms. Aiming at the deficiency of JS divergence, the paper consider from the three aspects of word frequency, text frequency and inverse category frequency corrected by coefficient of variation, the JS divergence is adjusted and corrected. The weights are introduced into the naive Bayes formula. Compared with other algorithms, it is proved that this method improves the naive Bias classification algorithm effectively. Therefore, compared with other classification algorithms, the performance of naive Bayesian classification algorithm based on JS divergence feature weighting is greatly improved.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-05-24 Cooperative journals: 《计算机应用研究》
Abstract： The traditional immune network optimization algorithm has the shortcomings of weak local searching ability, low precision and premature convergence. In order to improve the algorithm performance, this paper proposed an artificial-immune-network-based memetic algorithm for dynamic optimization problems. Based on the framework of memetic algorithm, an artificial immune network algorithm serves as the global search algorithm, and a tabu search algorithm serve as the local search operator. At the same time, the algorithm introduced the Cauchy variation to improve global searching ability and prevent premature convergence. The experimental results show that the improved algorithm has better search precision and convergence speed compared with other algorithms.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-05-20 Cooperative journals: 《计算机应用研究》
Abstract： Cross-site scripting is a common way of exploiting Web application security vulnerabilities. A malicious user exploits a vulnerability to inject a malicious script into a web page, and when the user browses the page, it triggers the script, causing the attack to occur. This paper studied a recursive feature elimination algorithm based on regular expression and support vector machine (RE-SVM-RFE) for each kind of deformation. Firstly, the regular expression matching algorithm, to select a representative training set of characteristics, i. e. , the data preprocessing; reuse RE-SVM-RFE feature selection algorithm to select the optimal characteristics, and then the keyword feature offensive sort. Finally, it summarized the frequency of occurrence of the keyword feature, found that the higher the frequency the greater the likelihood loopholes. Experimental results show that, after the data RE-SVM-RFE recursive feature elimination after SVM feature selection algorithm, higher accuracy of prediction, and better sensitivity and specificity, the algorithm can effectively detect XSS.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-04-19 Cooperative journals: 《计算机应用研究》
Abstract： Microblog platform contains potential user's information, through microblog data mining microblog user interest has important social significance. On account of the characteristics of user interest and microblog information, this paper put forward a method of microblog user interest mining based on text clustering and interest decay(TCID-MUIM) . Firstly, it used the synonyms combined strategy based on Tongyici Cilin to make up for the process of modeling the lack of word frequency information. Secondly, it used the double single-pass incomplete clustering algorithm to make up the problem that the microblog text was shorter so that difficult to dig the topic information. Finally, it used the LDA model modeling, as well as considering the user's interest changes with time, by introduction of time factor compresses the microblog-topic matrix into the user-topic matrix to gain user interest. Experimental results show that compared to traditional modeling methods and the modeling methods of merger user's all history microblog as the same document, the TCID-MUIM method presented which modeling results have a higher topic's differences and closer to the user's real interest preferences.
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