Bulk password grading priori check method

A verification method and password technology, applied in the field of information security, can solve the problems of relying on weak password dictionaries and accuracy dependence of Markov model method, and achieve the effect of effectively evaluating password strength and protecting the overall security of the system.

Active Publication Date: 2015-01-07
ZHEJIANG UNIV OF TECH
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Problems solved by technology

However, the accuracy of the Markov model method depends on the setting of the threshold
In addition, based on the Bloom filter, it can support the password strength judgment of complex patterns, but it is very dependent on the weak password dictionary

Method used

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  • Bulk password grading priori check method
  • Bulk password grading priori check method
  • Bulk password grading priori check method

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[0138] Import the real password data of 10 million Chinese users, apply this method to do 0.1% random sampling first (the degree of agreement between the classification effect and the complete password set training effect reaches 0.96), and obtain the second-order Markov probability transition matrix after training, and then import All 10 million passwords, starting with t 1 =0.2,t 2 =0.8 Set the threshold, divide into 3 levels, and decompose about 2 million, 6 million and 2 million passwords of the first level, second level and third level respectively. Corresponding to the use of three-stage Bloom filter, using the above nine hash functions, the false positive rate is 0.005, and the bit vector M of the first, second, and third-stage Bloom filter is calculated 1 , M 2 , M 3 24 million, 72 million, and 24 million bits, after obtaining the specific parameters of the 3-stage Bloom filter, initialize it. And map the corresponding password set to the corresponding Bloom filter...

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Abstract

A bulk password grading priori check method includes two steps of grading based on actual password data as well as training and retrieval of a grading password model. The grading includes the steps of firstly sampling and extracting millions of Chinese user password data to obtain a sample training set, then obtaining password probability transfer matrix through a second-order Markov model according to the sample training set and calculating to obtain a strength assessed value of each password, and finally grading all password data according to the password assessed value and a password hierarchy. The training and retrieval of the grading password model includes the steps of storing grading results at a bit vector of a Bloom filter at each grade through hash functions by building a password Bloom filter of different strength for the password set of each grade so as to build a grading password model, and using the password Bloom filters of multiple grades for quickly and efficiently determining the strength of passwords to be checked during retrieval.

Description

technical field [0001] The invention belongs to the field of information security. Background technique [0002] As a large number of users and applications access the Internet, passwords, as a low-cost system user authentication method commonly used at present, are crucial to system security. It can be predicted that password-based authentication will continue to be implemented for a long period of time in the future. Numerous password leak security incidents and literature show that domestic system administrators have major negligence in password management. On the other hand, domestic users lack detailed password setting guidance, resulting in a much higher proportion of users using weak passwords than international users. Therefore, systems with a large number of users in our country face higher risks in password security. Providing a regular and efficient hierarchical inspection and evaluation method for a large number of passwords can enhance the overall security of ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F21/31G06F17/30G06K9/66
CPCG06F21/46
Inventor 沈瑛廖刘承董天阳
Owner ZHEJIANG UNIV OF TECH
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