User Behavior Analysis for Detecting Compromised User Accounts: A Review Paper
, e
28 set 2023
INFORMAZIONI SU QUESTO ARTICOLO
Pubblicato online: 28 set 2023
Pagine: 102 - 113
Ricevuto: 05 lug 2023
Accettato: 18 ago 2023
DOI: https://doi.org/10.2478/cait-2023-0027
Parole chiave
© 2023 M. Jurišić et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
The rise of online transactions has led to a corresponding increase in online criminal activities. Account takeover attacks, in particular, are challenging to detect, and novel approaches utilize machine learning to identify compromised accounts. This paper aims to conduct a literature review on account takeover detection and user behavior analysis within the cybersecurity domain. By exploring these areas, the goal is to combat account takeovers and other fraudulent attempts effectively.