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Automatizované generování pravidel pro modifikaci hesel s využitím metod strojového učení
Šírová, Lucia ; Veselý, Vladimír (oponent) ; Hranický, Radek (vedoucí práce)
The success of password cracking using a dictionary attack is limited by the scope and quality of the used dictionary. One way to enhance the success rate of password cracking is to expand the dictionary with password mangling rules. These rules typically reflect human tendencies in password creation, such as appending numbers at the end of the password or capitalizing the first letter. This bachelor’s thesis describes a tool’s design and implementation process that aims to generate these rules by analysis of existing passwords, for example, from datasets obtained during security breaches. This tool enhances existing solutions by providing a choice of four distinct clustering methods. Unlike other rule-generating tools that leverage machine learning, it broadens the generated rules to nineteen unique types. Additionally, the tool offers customizable configurations for rule types and their priorities. Testing results suggest that the tool discussed in this bachelor’s thesis performs comparably or even better than a previously known state-of-the-art solutions.

Viz též: podobná jména autorů
7 SIROVÁ, Lucie
7 Šírová, Lucie
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