[1]常稼笙,雷良发,王 胜.基于 12306 用户支付账号的风险分析[J].计算机技术与发展,2022,32(S1):114-119.[doi:10. 3969 / j. issn. 1673-629X. 2022. S1. 024]
 CHANG Jia-sheng,LEI Liang-fa,WANG Sheng.Risk Analysis Based on 12306 User Payment Account[J].,2022,32(S1):114-119.[doi:10. 3969 / j. issn. 1673-629X. 2022. S1. 024]
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基于 12306 用户支付账号的风险分析()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
32
期数:
2022年S1期
页码:
114-119
栏目:
应用前沿与综合
出版日期:
2022-12-11

文章信息/Info

Title:
Risk Analysis Based on 12306 User Payment Account
文章编号:
1673-629X(2022)S1-0114-06
作者:
常稼笙1 雷良发1 王 胜2
1. 共致开源(北京)信息科技有限公司,北京 100085;
2. 中国铁道科学研究院 电子计算技术研究所,北京 100081
Author(s):
CHANG Jia-sheng1 LEI Liang-fa1 WANG Sheng2
1. Embracesource ( Beijing) Information Technology Co. ,Ltd. ,Beijing 100085,China;
2. Institute of Computing Technology,China Academy of Railway Sciences,Beijing 100081,China
关键词:
风险分析支付行为分析有监督学习分类模型算法12306
Keywords:
isk analysispayment behavior analysissupervised learningclassification model algorithm12306
分类号:
TP39
DOI:
10. 3969 / j. issn. 1673-629X. 2022. S1. 024
摘要:
近年来随着人民出行需求的不断增长,越来越多的人使用 12306 互联网售票系统购买火车票,由于铁路运力有限,春运节假日等高峰期,票源紧张,无法满足所有用户的出行需求,在此背景下第三方购票平台、黄牛党、抢票软件等利用自身技术优势,不断推出加价抢票服务,严重破坏了公平公正的售票环境,给 12306 售票系统的稳定运行带来了极大的风险。在此背景下,利用开源技术和大数据分析算法,对 12306 用户的支付行为进行了风险分析研究,并结合 12306 用户的历史支付信息,通过有监督的分类模型算法实现了正常支付账号和异常支付账号的分类,最终实现了对 12306 用户支付账号支付行为的风险分析预测。 建立了 12306 支付账号的特征计算体系,形成了 12306 支付账号风险识别的方法论。
Abstract:
In recent years,with the increasing of people’s travel demand,more and more people are using the 12306 Internet ticketingsystem to buy train ticket. Because of the limited railway transport capacity,spring festival travel rush and holidays,supporters strained,itcannot satisfy the travel needs of all users. In this context, third - party ticket platform, ticket scalper, ticket - snatching software takeadvantage of their technology to promote premium ticket services persistently, which seriously damaged? the fair and just ticketingenvironment and brought great risks to the stable operation of 12306 ticketing system. In this context,the risk analysis of 12306 users’payment behavior is carried out by using open source technology and big data analysis algorithm. Combined with the historical paymentinformation of 12306 users, the classification of normal payment accounts and abnormal payment accounts is realized through thesupervised classification model algorithm, and finally the risk analysis and prediction of payment behavior of 12306 users ’ paymentaccounts is realized. The characteristic calculation system of 12306 payment account is established, and the methodology of riskidentification of 12306 payment account is formed.

相似文献/References:

[1]罗佳 杨世平.基于熵权系数法的信息安全模糊风险评估[J].计算机技术与发展,2009,(10):177.
 LUO Jia,YANG Shi-ping.Fuzzy Risk Assessment for Information Security Based on Method of Entropy - Weight Coefficient[J].,2009,(S1):177.
[2]杨召. 基于蒙特卡洛的航次决策风险分析方法[J].计算机技术与发展,2015,25(04):34.
 YANG Zhao. Voyage Decision Risk Analysis Method Based on Monte Carlo[J].,2015,25(S1):34.

更新日期/Last Update: 2022-06-10