用于检测受损用户帐户的用户行为分析:一篇综述论文

IF 1.2 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS

Cybernetics and Information Technologies Pub Date : 2023-09-01 DOI:10.2478/cait-2023-0027

M. Jurišić, I. Tomičić, P. Grd

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引用次数: 0

摘要

随着网络交易的增多，网络犯罪活动也相应增多。账户接管攻击尤其难以检测，新方法利用机器学习来识别受损账户。本文旨在对网络安全领域的账户接管检测和用户行为分析进行文献综述。通过探索这些领域，目标是有效地打击账户接管和其他欺诈企图。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

User Behavior Analysis for Detecting Compromised User Accounts: A Review Paper

Abstract 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.

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来源期刊

Cybernetics and Information Technologies COMPUTER SCIENCE, INFORMATION SYSTEMS-

CiteScore

3.20

自引率

25.00%

发文量

审稿时长

12 weeks