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Password strength evaluation model based on ensemble learning

An evaluation model and integrated learning technology, applied in the field of information security, can solve the problems of poor versatility of the password evaluation model, and achieve the effects of high accuracy, high accuracy of evaluation results, and strong versatility

Inactive Publication Date: 2018-11-06
SICHUAN UNIV
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AI Technical Summary

Problems solved by technology

[0005] The existing password evaluation models have poor versatility, and there is no evaluation model that can be applied from simple passwords to very complex passwords

Method used

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  • Password strength evaluation model based on ensemble learning
  • Password strength evaluation model based on ensemble learning
  • Password strength evaluation model based on ensemble learning

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Experimental program
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Embodiment Construction

[0020] The model proposed in this paper is composed of four basic learners, which use different evaluation methods to evaluate the strength of the same password, and then obtain the final evaluation results through ensemble learning.

[0021] Such as figure 1 Shown is the overall architecture diagram of the system. Among them, the base learners include: evaluation learner based on blacklist password set, evaluation learner based on heuristic, evaluation learner based on Markov chain, PCFG learner, etc., and each base learner is independent of each other. The input password will enter each basic learner for evaluation at the same time, and output their respective evaluation scores S. Afterwards, input S into the respective determiners, and output the password determination result Labes after being judged by the respective judgers, wherein the result set Labes includes three labels: weak, medium and strong. According to the judgment results of each basic learner, the final eva...

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Abstract

The invention designs a password strength evaluation model based on multi-model ensemble learning. Firstly, a real password training set is used to train several existing password evaluation models assub-models. Secondly, several trained sub-models are used as base learners for ensemble learning, and the advantage integration of each sub-model is realized by the combination strategy of partial weak-term voting. Finally, a universal password evaluation model is implemented based on high accuracy. Password strength evaluation based on a multi-model ensemble learning model for passwords with different levels of complexity is performed, the evaluation results are high in accuracy and versatility, the multi-model ensemble learning has good applicability in password evaluation.

Description

technical field [0001] The invention belongs to the field of information security. Aiming at the problem that the existing password evaluation models are poor in versatility, and there is no evaluation model that can be used from simple passwords to very complex passwords, a password evaluation model based on multi-model ensemble learning is designed. Background technique [0002] In terms of application system authentication, password security is directly related to the security of the entire application system and the protection of user privacy. With the development of Internet services (such as mail, e-commerce, social networking, etc.), more and more network services require password protection. However, human beings have limited memory capacity, which leads users to inevitably use different degrees of weak passwords, or use the same password in different application systems, which brings serious security risks to application systems (such as social engineering attacks,...

Claims

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Application Information

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IPC IPC(8): G06F21/46
CPCG06F21/46
Inventor 方勇黄诚刘亮宋创创张成
Owner SICHUAN UNIV
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