Research Article
Learning Framework for Guessing Alphanumeric Passwords on Mobile Phones Based on User Context and Fragment Semantics
@INPROCEEDINGS{10.1007/978-3-031-56583-0_2, author={Lilian Noronha Nassif and Jonny Silva de Oliveira}, title={Learning Framework for Guessing Alphanumeric Passwords on Mobile Phones Based on User Context and Fragment Semantics}, proceedings={Digital Forensics and Cyber Crime. 14th EAI International Conference, ICDF2C 2023, New York City, NY, USA, November 30, 2023, Proceedings, Part II}, proceedings_a={ICDF2C PART 2}, year={2024}, month={4}, keywords={Digital Forensics Password Guessing Mobile Forensics}, doi={10.1007/978-3-031-56583-0_2} }- Lilian Noronha Nassif
Jonny Silva de Oliveira
Year: 2024
Learning Framework for Guessing Alphanumeric Passwords on Mobile Phones Based on User Context and Fragment Semantics
ICDF2C PART 2
Springer
DOI: 10.1007/978-3-031-56583-0_2
Abstract
When conducting a criminal investigation, accessing mobile phone data is crucial for law enforcement. However, encryption mechanisms and user locks are becoming increasingly complex and more challenging for forensic examiners. Although there are tools that can perform brute-force attacks to crack passwords on mobile phones, it becomes difficult when faced with alphanumeric passwords. The challenge is not only the algorithm but also the use of a customized dictionary. It is impractical to use a complete dictionary with all possible combinations as the attack conditions are very restrictive, and the time it takes to crack the password becomes too long depending on its length. In this article, we present a learning framework based on a set of dictionaries, variation rules, and fragment permutations. Dictionaries are organized from different perspectives of personal data, open sources, and groups of contexts. The naming and ordering of the dictionary help digital forensics examiners strategize and improve their chances of success in cracking alphanumeric passwords.
