Mitigating Online Sexual Grooming Cybercrime on Social Media Using Machine Learning: A Desktop Survey
Mitigating Online Sexual Grooming Cybercrime on Social Media Using Machine Learning: A Desktop Survey
复制标题
使用机器学习减轻社交媒体上的在线性诱骗网络犯罪：桌面调查
DOI：
10.1109/icabcd.2018.8465413
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
S. Lefophane
中科院分区：
文献类型：
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作者：
C. H. Ngejane;G. Mabuza;J. Eloff;S. Lefophane
社交媒体上出现了身份欺骗、网络欺凌、身份盗窃和在线性引诱等网络威胁。这些威胁令整个社会感到不安。对于接触互联网的未成年人来说更是如此，他们甚至可能没有意识到这些威胁。本文简要概述了为确保社交媒体上未成年人的安全而实施的网络安全方法的不同发展，特别是;在线性诱骗。本文提出了一个关于机器学习技术的桌面调查，用于检测在线性美容。其目的是巩固过去学者在这一研究领域所做的大部分工作，以发展对已提出的各种算法和报告的性能结果的见解。
Cyber threats such as identity deception, cyber bullying, identity theft and online sexual grooming have been witnessed on social media. These threats are disturbing to the society at large. Even more so to minors who are exposed to the Internet and might not even be aware of these threats. This paper describes a brief overview of different developments on cybersecurity methodologies that have been implemented to ensure safety of minors on social media, particularly; online sexual grooming. A desktop survey on Machine Learning technologies that have used to detect online sexual grooming is presented in this paper. The aim is to consolidate most of the work done in the past by scholars in this area of research, in order to develop insights on various algorithms that have been proposed and the reported performance results.