TY - JOUR
T1 - Detecting compromised accounts caused by phone number recycling on e-commerce platforms
T2 - taking Meituan as an example
AU - Gao, Min
AU - Chen, Shutong
AU - Gao, Yangbo
AU - Zhang, Zhenhua
AU - Chen, Yu
AU - Li, Yupeng
AU - Ye, Qiongzan
AU - Wang, Xin
AU - Chen, Yang
N1 - Project supported by the National Natural Science Foundation of China (Nos. 62072115, 62202402, 61971145, and 61602122), the Shanghai Science and Technology Innovation Action Plan Project (No. 22510713600), the Guangdong Basic and Applied Basic Research Foundation, China (Nos. 2022A1515011583 and 2023A1515011562), the One-off Tier 2 Start-up Grant (2020/2021) of Hong Kong Baptist University (Ref. RCOFSGT2/20-21/COMM/002), Startup Grant (Tier 1) for New Academics AY2020/21 of Hong Kong Baptist University and Germany/Hong Kong Joint Research Scheme sponsored by the Research Grants Council of Hong Kong, China, the German Academic Exchange Service of Germany (No. G-HKBU203/22), and Meituan
Publisher Copyright:
© Zhejiang University Press 2024.
PY - 2024/8/30
Y1 - 2024/8/30
N2 - Phone number recycling (PNR) refers to the event wherein a mobile operator collects a disconnected number and reassigns it to a new owner. It has posed a threat to the reliability of the existing authentication solution for e-commerce platforms. Specifically, a new owner of a reassigned number can access the application account with which the number is associated, and may perform fraudulent activities. Existing solutions that employ a reassigned number database from mobile operators are costly for e-commerce platforms with large-scale users. Thus, alternative solutions that depend on only the information of the applications are imperative. In this work, we study the problem of detecting accounts that have been compromised owing to the reassignment of phone numbers. Our analysis on Meituan’s real-world dataset shows that compromised accounts have unique statistical features and temporal patterns. Based on the observations, we propose a novel model called temporal pattern and statistical feature fusion model (TSF) to tackle the problem, which integrates a temporal pattern encoder and a statistical feature encoder to capture behavioral evolutionary interaction and significant operation features. Extensive experiments on the Meituan and IEEE-CIS datasets show that TSF significantly outperforms the baselines, demonstrating its effectiveness in detecting compromised accounts due to reassigned numbers.
AB - Phone number recycling (PNR) refers to the event wherein a mobile operator collects a disconnected number and reassigns it to a new owner. It has posed a threat to the reliability of the existing authentication solution for e-commerce platforms. Specifically, a new owner of a reassigned number can access the application account with which the number is associated, and may perform fraudulent activities. Existing solutions that employ a reassigned number database from mobile operators are costly for e-commerce platforms with large-scale users. Thus, alternative solutions that depend on only the information of the applications are imperative. In this work, we study the problem of detecting accounts that have been compromised owing to the reassignment of phone numbers. Our analysis on Meituan’s real-world dataset shows that compromised accounts have unique statistical features and temporal patterns. Based on the observations, we propose a novel model called temporal pattern and statistical feature fusion model (TSF) to tackle the problem, which integrates a temporal pattern encoder and a statistical feature encoder to capture behavioral evolutionary interaction and significant operation features. Extensive experiments on the Meituan and IEEE-CIS datasets show that TSF significantly outperforms the baselines, demonstrating its effectiveness in detecting compromised accounts due to reassigned numbers.
KW - Compromised account detection
KW - E-commerce
KW - Neural networks
KW - Phone number recycling
KW - TP391
UR - http://www.scopus.com/inward/record.url?scp=85202770558&partnerID=8YFLogxK
U2 - 10.1631/FITEE.2300291
DO - 10.1631/FITEE.2300291
M3 - Journal article
AN - SCOPUS:85202770558
SN - 2095-9184
VL - 25
SP - 1077
EP - 1095
JO - Frontiers of Information Technology and Electronic Engineering
JF - Frontiers of Information Technology and Electronic Engineering
IS - 8
ER -