Data protection method, electronic device and computer program product

Patent metadata

Field	Value
Publication number	US-11940879-B2
Application number	US-202017060040-A
Country	US
Kind code	B2
Filing date	Sep 30, 2020
Priority date	Aug 7, 2020
Publication date	Mar 26, 2024
Grant date	Mar 26, 2024

Abstract

Embodiments of the present disclosure provide a data protection method, an electronic device, and a computer program product. The method includes determining an object feature for each protection object in a set of protection objects that generate protected data, the set of protection objects including at least one protection object configured with a predetermined data protection strategy. The method further includes determining a set of candidate objects belonging to the same class as the at least one protection object from the set of protection objects according to the determined object features. The method further includes configuring the predetermined data protection strategy to at least one candidate object in the set of candidate objects.

First claim

The invention claimed is:

1. A data protection method, comprising:
determining an object feature for each protection object in a set of protection objects to obtain determined object features, the set of protection objects comprising a protection object configured with a predetermined data protection strategy, wherein the protection object comprises a predetermined attribute, an external attribute, and an internal attribute, wherein the set of protection objects comprises at least one of the following: a virtual machine, a database, a physical device, or a file system, and wherein the predetermined attribute specifies one of an operating system of the protection object, a size of storage devices of the protection object, and a number of processing units of the protection object;
monitoring the protection object from outside of the operating system of the protection object to obtain the external attribute;
logging into the operating system of the protection object to obtain the internal attribute;
training a classification model based on a corresponding object feature of the protection object, wherein the classification model comprises a support vector machine, wherein the object feature of the protection object comprises a plurality of feature items;
determining, using the classification model, a set of candidate objects belonging to a same class as the protection object according to the determined object feature of the protection object;
ranking the set of candidate objects according to the plurality of feature items to obtain a set of ranked candidate objects;
determining at least one candidate object based on the set of ranked candidate objects; and
configuring the predetermined data protection strategy to include the at least one candidate object.

2. The method according to claim 1 , wherein determining the at least one candidate object based on the set of ranked candidate objects comprises:
providing a user with the set of ranked candidate objects;
receiving a user selection indicating the at least one candidate object; and
updating the classification model using the user selection.

3. The method according to claim 1 , wherein determining the object feature for each protection object in the set of protection objects comprises:
clustering the set of protection objects based on a set of attributes of each protection object in the set of protection objects; and
determining the object feature of each protection object based on the set of attributes and a result of the clustering.

4. A non-transitory computer readable medium comprising instructions which, when executed by a computer processor, enables the computer processor to perform a method, the method comprising:
determining an object feature for each protection object in a set of protection objects to obtain determined object features, the set of protection objects comprising a protection object configured with a predetermined data protection strategy, wherein the protection object comprises a predetermined attribute, an external attribute, and an internal attribute, wherein the set of protection objects comprises at least one of the following: a virtual machine, a database, a physical device, or a file system, and wherein the predetermined attribute specifies one of an operating system of the protection object, a size of storage devices of the protection object, and a number of processing units of the protection object;
monitoring the protection object from outside of the operating system of the protection object to obtain the external attribute;
logging into the operating system of the protection object to obtain the internal attribute;
training a classification model based on a corresponding object feature of the protection object, wherein the classification model comprises a support vector machine, wherein the object feature of the protection object comprises a plurality of feature items;
determining, using the classification model, a set of candidate objects belonging to a same class as the protection object according to the determined object feature of the protection object;
ranking the set of candidate objects according to the plurality of feature items to obtain a set of ranked candidate objects;
determining at least one candidate object based on the set of ranked candidate objects; and
configuring the predetermined data protection strategy to include the at least one candidate object.

Assignees

• Emc Ip Holding Co Llc

Inventors

• Chen Qiang
• Yu Jing
• Xu Jiayang
• Sha Danqing

Classifications

• G06F11/1451 Primary

  by selection of backup contents · CPC title

• G06N20/00

  Machine learning · CPC title

• G06F2201/84

  Using snapshots, i.e. a logical point-in-time copy of the data · CPC title

• G06F11/1448 Primary

  Management of the data involved in backup or backup restore · CPC title

• G06N20/10 Primary

  using kernel methods, e.g. support vector machines [SVM] · CPC title