账号混乱度检测数据

在互联网实务中，各类平台中的风险账号通常是由机器随机生成并批量注册，由此，这些风险账号所包含的字符串中的字符排列较为混乱；而对用户账号的混乱度进行量化处理并得到混乱度，有助于快速初步判断该用户账号是否为风险账号。1.对用户账号集合中的用户账号字符串进行统计、分析，构建字符串表；
2.对目标用户账号进行切分处理得到若干个目标字符串；
3.将上述若干个目标字符串与字符串表进行匹配，得出能匹配到上述字符串表中的字符串数量和各个字符串的长度；
4.基于匹配到的字符串数量和各个字符串的长度计算平均长度；
5.取平均长度的倒数作为目标用户账号的混乱度。

In practical internet scenarios, risk accounts on various platforms are typically randomly generated and bulk-registered by machines, resulting in chaotic character arrangements in their associated strings. Quantifying the disorder degree of user accounts to obtain a quantifiable disorder score enables quick and preliminary judgment of whether a user account is a risk account.
1. Perform statistical analysis on the user account strings in the user account collection, and construct a string lookup table;
2. Segment the string of the target user account to obtain multiple target substrings;
3. Match these obtained target substrings against the constructed string lookup table, and acquire the count of successfully matched substrings and the length of each matched substring;
4. Calculate the average length of the matched substrings based on their total quantity and individual lengths;
5. Take the reciprocal of the calculated average length as the disorder degree of the target user account.

搜集汇总

数据集介绍

特点

该数据集名为'账号混乱度检测数据'，由网易（杭州）网络有限公司申请，包含113条数据，用于检测互联网平台中账号的混乱度，以判断账号是否为风险账号。数据集提供了示例数据和算法规则，应用场景为风险账号的初步判断。