Malicious Account Detection based on intelligent algorithm Research

Xun Huang, Haibo Luo
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Abstract

Malicious account detection has always been a hot issue. This paper mainly identifies the malicious account at the registration level. After feature extraction of the collected data, a weighted undirected graph is constructed. Node2Vec is used to convert each node into a multidimensional vector. K-means algorithms and DBSCAN algorithms are used to obtain the model of garbage account. Finally, Euclidean distance is used to identify whether the malicious account is.
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基于智能算法的恶意账户检测研究
恶意账户检测一直是一个热点问题。本文主要对注册级恶意账号进行识别。对采集到的数据进行特征提取后,构造加权无向图。Node2Vec用于将每个节点转换为多维向量。采用K-means算法和DBSCAN算法获得垃圾账户模型。最后利用欧几里得距离来识别恶意账号是否存在。
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