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A Systematic Review on Password Guessing Tasks.

Wei Yu1, Qingsong Yin2, Hao Yin1

  • 1The 30th Research Institute of China Electronics Technology Group Corporation, Chuangye Road, Chengdu 610093, China.

Entropy (Basel, Switzerland)
|September 28, 2023
PubMed
Summary

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This review analyzes over thirty password guessing algorithms from 2016-2023, categorizing them and providing a benchmark dataset. It highlights trends, challenges, and future research directions in cybersecurity.

Area of Science:

  • Computer Science
  • Cybersecurity
  • Information Security

Background:

  • Password guessing algorithms pose a significant threat to cybersecurity.
  • Numerous methods have been developed, necessitating a comprehensive overview.

Purpose of the Study:

  • To systematically review password guessing methods published between 2016 and 2023.
  • To establish a classification taxonomy and create a benchmark dataset.
  • To identify trends, challenges, and future research directions in the field.

Main Methods:

  • Systematic literature review of over thirty password guessing algorithms.
  • Development of a taxonomy classifying methods into trawling and targeted guessing.
  • Bibliometric analysis of research trends and inter-paper citations.
Keywords:
deep learningpassword guessingtargeted password guessingtrawling password guessing

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  • Creation of an extensive benchmark dataset for future research.

    • Main Results:

    • A comprehensive review and classification of contemporary password guessing techniques.
    • A novel benchmark dataset to facilitate reproducible research.
    • Insights into research trends, including the integration of deep learning.

    Conclusions:

    • Password guessing remains a critical cybersecurity challenge.
    • Future research should focus on diverse scenarios, efficiency, and hybrid AI approaches.
    • The provided dataset and analysis will guide future cybersecurity advancements.