基于人工智能的社会工程监控系统

K. Yapa, S. Udara, U. P. B. Wijayawardane, K. N. P. Kularatne, N. M. P. P. Navaratne, W. G. V. U. Dharmaphriya
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引用次数: 1

摘要

社交媒体是全球个人使用最广泛的在线平台之一。然而,这些社交媒体用户中很少有人被教育过不自觉地使用社交媒体的不良影响。因此,这个研究项目,是为了开发一个咨询系统,以造福那些在社交媒体上无知和健忘的行为所造成的不利影响的受害者。该系统采用自定义数据集,采用决策树模型实现;对于后续的操作实现,使用了Python编程语言、Pandas、自然语言处理和TensorFlow。该咨询系统可以监控用户行为,并根据用户在社交媒体上的行为类别和级别,为用户生成定制化的感知报告。此外,系统还能够生成使用行为波动的图形报告,供用户参考。通过这些定制的意识报告和图表报告,用户可以识别自己的潜在漏洞,并改善他们的社交媒体习惯。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
AI Based Monitoring System for Social Engineering
Social media is one of the most predominantly used online platforms by individuals across the world. However, very few of these social media users are educated about the adverse effects of obliviously using social media. Therefore, this research project, is to develop an advisory system for the benefit of the general public who are victimized by the adverse impacts of their ignorant and oblivious behavior on social media. The system was implemented using a decision tree model with the use of customized datasets; and for the proceeding operational implementations, Python programming language, Pandas, Natural Language Processing and TensorFlow were used. This advisory system can monitor user behaviors and generate customized awareness reports for the users based on category and level of their behaviors on social media. Furthermore, the system is also capable of generating graph reports of the use behavior fluctuations for the reference of the user. With the help of these customized awareness reports and the graph reports, the users can identify their potential vulnerabilities and improve their social media habits.
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