可扩展的学习框架,用于检测新的类型的Twitter垃圾邮件与滥用和异常检测检测
Jaeun Choi1, Byunghwan Jeon2, Chunmi Jeon3
1College of Business, Kwangwoon University, Seoul 01897, Republic of Korea.
Sensors (Basel, Switzerland)
|April 13, 2024
概括
这项研究引入了一个新的框架,通过识别异常的推特来检测新的Twitter垃圾邮件. 它改进了现有的方法,首先识别已知的垃圾邮件,然后模拟正常的推特,以便更好地检测和更少的假阳性.
科学领域:
- 计算机科学 计算机科学
- 社交媒体分析 社交媒体分析
- 网络安全 网络安全
背景情况:
- 社交媒体平台面临着越来越多的垃圾邮件扩散.
- 现有的垃圾邮件检测系统与新的垃圾邮件类型作斗争.
- 开发有效的对策对于平台的完整性至关重要.
研究的目的:
- 提出一种基于异常检测的框架,用于识别新的Twitter垃圾邮件.
- 为了提高垃圾邮件检测率和减少错误的阳性.
- 为不断发展的垃圾邮件策略创造一个适应性的框架.
主要方法:
- 模拟非垃圾邮件推特的特征,以识别偏差.
- 使用决策树预先检测已知的垃圾邮件.
- 采用一级支持向量机和自动编码器用于异常检测.
- 为适应性调整检测错误成本.
主要成果:
- 拟议的框架显示,与传统方法相比,未知垃圾邮件的检测率更高.
- 保持对已知垃圾邮件的同等或改进的检测和错误阳性率.
- 能够适应不断变化的垃圾邮件条件.
结论:
- 异常检测,当与已知垃圾邮件的预检测相结合时,可以有效地识别Twitter上的新浪垃圾邮件.
- 该框架为应对不断变化的垃圾邮件威胁提供了强大而适应性的解决方案.
- 这种方法平衡了检测准确度和可管理的假阳性率.
相关概念视频
01:18Steps in Outbreak Investigation
125
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
125
01:22Statistical Package for the Social Sciences (SPSS)
318
The Statistical Package for the Social Sciences, or SPSS, is a data management and analysis software suite. Developed by SPSS Inc. in 1968 and acquired by IBM in 2009, this tool was initially designed for social science data analysis, evolving to serve a wider range of disciplines. It was later renamed to Statistical Product and Service Solutions.
SPSS streamlines the process from data preparation to analysis and reporting. It is characterized by its user-friendly interface, which conceals...
SPSS streamlines the process from data preparation to analysis and reporting. It is characterized by its user-friendly interface, which conceals...
318