Research On Efficient Dictionary Generation Method In Password Recovery

As of 2018,mobile Internet users reached 1.55 billion,and mobile Internet applications are increasingly integrated into Chinese life.At the same time,the development of mobile Internet has produced thinking about information security.Passwords are the most widely used authentication method in information security.Password recovery and encryption complement each other and it have also developed rapidly.The study found that the focus of password recovery is on the selection of the dictionary.However,with the increasing number of mobile Internet users,password space is exploding,dictionary files are getting larger and larger,and the number of candidate passwords in files has increased dramatically.Therefore,it is important to study the generation of efficient dictionaries in password recovery.In view of the large search space and low efficiency of dictionary files in password recovery,this thesis focuses on the password structure with high probability and the password set based on personal informa tion.On the basis of the probability context-free grammar,it is nearly 70 million in the real scene.The plaintext password has studied various distribution parameters and summarized the distribution rules of several high probability passwords.Based on these statistical characteristics and rules,the password gene pool model is proposed.The probability distribution is used to reduce the password search space.Two efficient dictionary generation algorithms are designed.The main tasks completed are as fo llows:1.The password gene library model is proposed.For the nearly 70 million real plaintext passwords,their distribution characteristics are counted,and several rules for generating high probability passwords are summarized.At the same time,the personal information in the password is analyzed,and the relationship between personal information and password is given.Based on these rules and relationships,the password strength calculation rules are designed.The password structure,numeric string,uppercase and lowercase letter strings and special string gene library model are proposed.2.Based on the password gene pool model,two high-probability dictionary generation algorithms based on walking attack and directed attack are proposed—the gene library-based password structure dictionary generation algorithm and the personal information-based dynamic password dictionary generation algorithm.The first algorithm uses a high-probability string gene to reorganize the password structure,avoiding the exhaustion of low-probability string parts and improving the dictionary hit rate.The second algorithm utilizes the correlation between the password and the personal information to generate a set of candidate passwords and improve the password hit rate.3.Password recovery experiments based on heterogeneous high performance computing platforms.On the same data set,compare the classic dictionary with the password recovery field.The experimental results show that the dictionary generated by the algorithm effectively improves the hit rate of the password.And it has been put into practical use in the password recovery project.