Anomaly object detection strategy generation method and device, electronic equipment and storage medium

CN122247708APending Publication Date: 2026-06-19BEIJING BAIDU NETCOM SCI & TECH CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
BEIJING BAIDU NETCOM SCI & TECH CO LTD
Filing Date
2026-03-31
Publication Date
2026-06-19

AI Technical Summary

Technical Problem

Existing risk control rule engine systems that rely on human experience are unable to quickly adapt to changes in fraud methods, resulting in delayed identification and an inability to effectively identify hidden fraud patterns. Furthermore, manual analysis is inefficient and has limited coverage, making it impossible to respond to new fraud patterns in a timely manner, which leads to losses for enterprises or individuals.

Method used

By analyzing the differences in the feature dimension distribution between historical object groups and suspicious object subgroups, an abnormal object detection strategy is automatically generated. The target feature dimension is determined from the candidate feature dimensions using the distribution difference information, and the abnormal object detection strategy is generated, which instructs the determination of whether the object to be verified is an abnormal object based on the dimension threshold.

Benefits of technology

It enables rapid and automated generation of anti-fraud strategies, improves the efficiency and accuracy of identifying abnormal objects, reduces marketing costs, and enhances user experience.

✦ Generated by Eureka AI based on patent content.

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Abstract

This disclosure provides a method for generating anomaly detection strategies, relating to the field of computer technology, particularly to the fields of the Internet, big data, and network security. The specific implementation scheme is as follows: based on the distribution data of multiple first feature dimensions and multiple second feature dimensions for multiple candidate feature dimensions, multiple distribution difference information is determined for each of the multiple candidate feature dimensions; based on the multiple distribution difference information, at least one target feature dimension is determined from the multiple candidate feature dimensions; based on the at least one target feature dimension, at least one anomaly detection strategy is generated, the anomaly detection strategy indicating whether the object to be verified is an anomaly object based on a dimension threshold for the target feature dimension and verification information of the object to be verified for the target dimension value. This disclosure also provides an anomaly detection strategy generation apparatus, an electronic device, and a storage medium.
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