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Dynamic Task Scheduler for Real Time Requirement in Cloud Computing System Read chapter Read first chapter

2018 | OriginalPaper | Chapter

User Password Intelligence Enhancement by Dynamic Generation Based on Markov Model

Authors : Zhendong Wu, Yihang Xia

Published in: Algorithms and Architectures for Parallel Processing

Publisher: Springer International Publishing

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Abstract

The use of passwords in daily life has become more and more widespread, which has become an indispensable part of life. However, there are still some security risks when using passwords. These security risks occupy a large part due to users using low strength password because of the very limited memory ability of human beings. It makes verbal guessing based on human memory habits achieve good attack effectiveness. In order to improve the security of network password system, this paper proposes a password enhancement method combining Markov model intelligent prediction and dynamic password enhanced technology. This method can greatly increase the password strength by more than 80% without increasing the memory burden of the user. At the same time, it does not need to store complex keys in the system, which can significantly improve the security of the network password system.

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Metadata
Title
User Password Intelligence Enhancement by Dynamic Generation Based on Markov Model
Authors
Zhendong Wu
Yihang Xia
Copyright Year
2018
Book
Algorithms and Architectures for Parallel Processing

Print ISBN: 978-3-030-05062-7

Electronic ISBN: 978-3-030-05063-4

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-030-05063-4_25

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