Object detection method and data storage unit detection method
By assigning a set of network addresses to each target object and using encoding rules to detect abnormal network addresses, the problem of the inability to quickly identify network attacks in existing technologies is solved, thus achieving efficient protection of cloud products.
CN122372231APending Publication Date: 2026-07-10ALIBABA CLOUD COMPUTING CO LTD
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- ALIBABA CLOUD COMPUTING CO LTD
- Filing Date
- 2025-01-08
- Publication Date
- 2026-07-10
AI Technical Summary
Technical Problem
Existing technologies are unable to quickly and accurately identify targets under cyberattacks, which affects the availability of cloud products.
Method used
By assigning a corresponding set of network addresses to each target object and using anomaly detection and encoding rules, the set of abnormal network addresses can be determined, thereby locating the abnormal object.
Benefits of technology
It enables rapid identification and isolation of network attacks, reduces the downtime and impact of cloud products, and improves the accuracy of attack identification.
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Figure CN122372231A_ABST
Abstract
This specification provides an object detection method and a data storage unit detection method. The object detection method includes: performing anomaly detection on multiple network addresses to determine abnormal network addresses, wherein any one of the multiple network addresses exists in at least two network address sets corresponding to target objects, and each target object corresponds to a network address set; determining an abnormal network address set based on the abnormal network addresses and the association between the multiple network addresses and the network address sets, and identifying the target objects corresponding to the abnormal network address sets as abnormal objects; thereby accurately and quickly locating abnormal objects that have suffered network attacks, avoiding the problem of not being able to accurately identify abnormal objects that have suffered network attacks.
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