Wi-Fi Handshake: analysis of password patterns in Wi-Fi networks.

Adrian Carballal, J Pablo Galego-Carro, Nereida Rodriguez-Fernandez, Carlos Fernandez-Lozano
Author Information
  1. Adrian Carballal: Department of Computer Science and Information Technologies, Faculty of Computer Science, CITIC-Research Center of Information and Communication Technologies, Universidade da Coruña, A Coruña, A Coruña, Spain. ORCID
  2. J Pablo Galego-Carro: Computer Architecture Group, Faculty of Computer Science, Universidade da Coruña, A Coruña, Spain.
  3. Nereida Rodriguez-Fernandez: Department of Computer Science and Information Technologies, Faculty of Communication Science, CITIC-Research Center of Information and Communication Technologies, Universidade da Coruña, A Coruña, Spain.
  4. Carlos Fernandez-Lozano: Department of Computer Science and Information Technologies, Faculty of Computer Science, CITIC-Research Center of Information and Communication Technologies, Universidade da Coruña, A Coruña, A Coruña, Spain. ORCID

Abstract

This article seeks to provide a snapshot of the security of Wi-Fi access points in the metropolitan area of A Coruña. First, we discuss the options for obtaining a tool that allows the collection and storage of auditable information from Wi-Fi networks, from location to signal strength, security protocol or the list of connected clients. Subsequently, an analysis is carried out aimed at identifying password patterns in Wi-Fi networks with WEP, WPA and WPA2 security protocols. For this purpose, a password recovery tool called Hashcat was used to execute dictionary or brute force attacks, among others, with various word collections. The coverage of the access points in which passwords were decrypted is displayed on a heat map that represents various levels of signal quality depending on the signal strength. From the handshakes obtained, and by means of brute force, we will try to crack as many passwords as possible in order to create a targeted and contextualized dictionary both by geographical location and by the nature of the owner of the access point. Finally, we will propose a contextualized grammar that minimizes the size of the dictionary with respect to the most used ones and unifies the decryption capacity of the combination of all of them.

Keywords

Associated Data

figshare | 10.6084/m9.figshare.19362971.v1

References

  1. PeerJ Comput Sci. 2021 Feb 3;7:e362 [PMID: 33817012]
  2. PeerJ Comput Sci. 2021 Aug 16;7:e678 [PMID: 34497871]

Word Cloud

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