Home // INNOV 2023, The Twelfth International Conference on Communications, Computation, Networks and Technologies // View article

The Past and Possible Future Development of Password Guessing

Authors:
Zelong Li
Teng Liu
Lei Li

Keywords: deep learning; generative models; neural networks; normalization methods; network and information security

Abstract:
According to the China Internet Network Information Center (CNNIC), by December 2022, the number of Internet users in China has reached 1.067 billion. Recently, consulting firm Kepios pointed out that nearly 5 billion people worldwide are currently active on social networks. Nowadays although there are many methods of identity authentication: fingerprint recognition, facial recognition and static password, static password is still the most widely used identity authentication method. Most people usually set passwords too simple and easily cracked. This allows attackers to crack their passwords with less cost. Password guessing technology can generate large-scale password dictionaries, which can be used to evaluate the strength of passwords and encourage users to change their own passwords. With the development of deep learning, password guessing technology is also constantly breaking through. But few people provide systematic surveys, which allow us to systematically review the most advanced methods and avoid repetitive research. Firstly, we will conduct a comprehensive analysis of the development of password guessing technology to this day. Secondly, we will propose future feasibility research methods based on the latest technology to address the shortcomings of password guessing models.

Pages: 14 to 23

Copyright: Copyright (c) IARIA, 2023

Publication date: November 13, 2023

Published in: conference

ISSN: 2326-9286

ISBN: 978-1-68558-104-6

Location: Valencia, Spain

Dates: from November 13, 2023 to November 17, 2023