Harder, better, faster, stronger: Optimising the performance of context-based password cracking dictionaries. (March 2023)

• Record Type: Journal Article
• Authors: Kanta, Aikaterini; Coisel, Iwen; Scanlon, Mark
• Is Part Of: Forensic science international. Volume 44(2023)Supplement
• Publication Date: 2023-03
• Subjects: Dictionary -- Contextual information -- Password cracking -- Wordlist
• DOI: 10.1016/j.fsidi.2023.301507
• Languages: English
• ISSNs: 2666-2817

Abstract

Abstract: Passwords have been the prevailing method of authentication since their inception more than 50 years ago, a trend which has no signs of slowing down in the foreseeable future. They are an integral part of the security of digital persons, systems and critical data, and yet, they often remain the weakest entry point to a digital system. A password itself is indeed an extension of its creator and therefore can be exploited by malicious actors leveraging available contextual information about a target password creator. Recent research has shown that bespoke password candidate lists, generated based on available contextual information, can positively impact the password cracking processes. This paper introduces an innovative methodology for composing a contextual wordlist and ranking the password candidates in order to maximise the chance of early success. The aim of the proposed approach is to support digital forensic investigators in their criminal investigation – especially when time is of the essence. This paper describes the implementation of this methodology and provides an overview of several experimental results demonstrating the advantages of this approach. These results demonstrate that by going through a harder, more rigorous password candidate selection process, better dictionaries can be generated that, in a faster timeframe, can crack stronger passwords.