Xiaoling Feng
ABSTRACT
This paper presents a method that helps e-commercial enterprises enhance risk control capabilities and operate anti-fraud during online marketing events. By definition, Malicious SIM Cards (MSCs) identification in this paper aims to identify SIM cards which are utilized by malicious purposes on specified terminals at scale (e.g., SIM modem pool or bulk SMS machine), and behave significantly different from normal SIM cards, especially towards e-commercial companies' marketing events, e.g., releases of coupons. The proposed MSC identification method is implemented as a label-function-based factor matrix framework. Particularly, a set of label functions is constructed from six dimensions via telecom big data analytics, including frequency of replacement, location, card type, Call Detail Records (CDRs), ID type, in-network-period in terms of SIM cards. Subsequently, MSC labels are provided to the identified SIM cards among the entire China Unicom SIM cards, which realize an effective way for large scale commercial use. Finally, selected features' distribution of MSCs identified and normal SIM cards are illustrated for comparison purposes.
- Wang, Y., Lu, J., Wu, Z.W., Lu, Y. (2006). Component Based Security Control for Information Network. 10.1109/CESA.2006.4281849.Google Scholar
- Wani, A., Sathiya, R., Geetha, A. (2017). A Survey of Applications and Security Issues in Software Defined Networking. International Journal of Computer Network and Information Security. 3. 21--28. 10.5815/ijcnis.2017.03.03.Google Scholar
- Ban, H., Seo, S., Park, J. Y., Won, S., Lee, K. (2019). Uncertainty estimation of exposure factors for consumer products based on various sample sizes. Food and Chemical Toxicology. 134. 110874. 10.1016/j.fct.2019.110874.Google Scholar
- Alibaba. 2019. Alibaba.com. (2019). Retrieved November 4, 2019 from https://ejointech.en.alibaba.com/product/60525374344-213942124/sms_gsm_gateway_32_channel_256_sim_cards_voip_sip_voice_gateway.htmlGoogle Scholar
- DU. Y. 2018. Research on Internet underground economy industry chain. Master's thesis. College of Economics, ZheJiang University, ZheJiang, China.Google Scholar
- Yang Yang. 2019. Pinduoduo suffers huge losses due to technical bug. (January 2019). Retrieved November 2, 2019 from http://www.chinadaily.com.cn/a/201901/20/WS5c4418a7a3106c65c34e5701.htmlGoogle Scholar
- Sun, M.Y., Shi, Z.S., Chen, S.J., Zhou, Z.B., Duan, Y.C. (2017). Energy-Efficient Composition of Configurable Internet of Things Services. IEEE Access. PP. 1--1. 10.1109/ACCESS.2017.2768544.Google ScholarCross Ref
- Liu, J., Ji, K., Sun, R.Y., Ma, K., Chen, Z.X., Wang. L. (2019). Abnormal Phone Analysis Based on Learning to Rank and Ensemble Learning in Environment of Telecom Big Data. In Proceedings of the 2019 11th International Conference on Machine Learning and Computing (ICMLC '19). ACM, New York, NY, USA, 301--305. DOI: https://doi.org/10.1145/3318299.3318349.Google ScholarDigital Library
- Wu, C.T., Yu, K., Wu, X.F. (2018). Scalping Anomaly Detection Based on Mobile Internet Traffic Data. In Proceedings of the 2nd International Conference on Telecommunications and Communication Engineering (ICTCE 2018). ACM, New York, NY, USA, 237--244. DOI: https://doi.org/10.1145/3291842.3291905.Google ScholarDigital Library
- Lin, X., Wang, Z., Huang, J. 2019. A kind of black production account recognition methods and equipment based on time flow feature (Mar. 2019). Patent No. CN109525595A, Filed December 25th., 2018, Issued Mar. 26th., 2019.Google Scholar
- Ji, S., Liu, Q., Chen, J., Wu, Y. 2018. E-commerce black-gray industry public opinion automatic mining method and system (Oct. 2018). Patent No. CN108647225A, Filed March 23rd., 2018, Issued Oct.12th., 2018.Google Scholar
- Dong, C., Jiang, X., Zhao, Y. 2019. A kind of grey black produces the keyword lookup method of popularization. (Jun. 2019). Patent No. CN109947913A, Filed January 26th., 2019, Issued Jun. 28th., 2019.Google Scholar
- Alexander, R., Stephen, B., Henry, E., Jason, F., Sen, W., Christopher, R. (2019). Snorkel: rapid training data creation with weak supervision. The VLDB Journal. 10.1007/s00778-019-00552-1Google Scholar
Index Terms
- Malicious SIM Cards Identification Method Based on Telecom Big Data Analytics
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