.png){kind=icon}
返回
A Risk Analysis Framework for Social Engineering Attack Based on User Profiling
.png){kind=icon}
OA
AI
DOI：10.4018/JOEUC.2020070104.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Social engineering attacks are becoming serious threats to cloud service. Social engineering attackers could get Cloud service custom privacy information or attack virtual machine images directly. Existing security analysis instruments are difficult to quantify the social engineering attack risk, resulting in invalid defense guidance for social engineering attacks. In this article, a risk analysis framework for social engineering attack is proposed based on user profiling. The framework provides a pathway to quantitatively calculate the possibility of being compromised by social engineering attack and potential loss, so as to effectively complement current security assessment instruments. The frequency of related operations is used to profile and group users for respective risk calculation, and other features such as security awareness and capability of protection mechanism are also considered. Finally, examples are given to illustrate how to use the framework in actual scenario and apply it to security assessment.
Keyword:
Authority
Cloud Security
Network Security Assessment
Operating Frequency
Risk Analysis
Social Engineering
User Profiling
Vulnerability
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.4
论文数:
561
被引数:
1.2K
机构
引用论文
LED: A fast overlapping communities detection algorithm based on structural clustering.png)
NEUROCOMPUTINGOAAI
NEUROCOMPUTINGIF6.5
OAAI分享收藏Automated Insider Threat Detection System Using User and Role-Based Profile Assessment使用基于用户和角色的配置文件评估的自动化内部威胁检测系统OAAI
OAAI分享收藏 没有更多内容
没有更多内容