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Context-Based Password Cracking for Digital Investigation
Congratulations to Aikaterini Kanta on the publication of Context-Based Password Cracking for Digital Investigation in School of Computer Science, University College Dublin.
Co-authors: none listed.
AI-generated summary of the contribution: This thesis investigates the hypothesis that bespoke password candidate lists, generated based on available contextual information, can positively impact the password cracking process. A methodology and framework for creating and assessing custom dictionary wordlists for dictionary-based password cracking attacks are introduced, with a specific focus on leveraging contextual information. The approach is designed to support digital forensic investigators in their criminal investigation, especially when time is of the essence. The thesis presents a detailed explanation of the framework’s implementation and demonstrates its benefits with the use of test cases. The results show that the proposed approach achieved very promising improvements over existing, traditional approaches, with over 50% improvement in some instances.