Abstract: A method, an electronic device, and a computer program product for storage management are provided. The method includes: acquiring a lock attribute record in a lock attribute record chain from a data protection network for backing up data, data protection servers of the data protection network reaching a consensus on the lock attribute record chain, the lock attribute record including a first attribute value of an attribute of a lock operation, the lock operation being used for preventing a backup of the data stored in a storage server from being tampered with; acquiring, based on the lock attribute record, a second attribute value of the attribute of the lock operation from the storage server; and generating, based on determining that the first attribute value does not match the second attribute value, an alarm indicating that the backup is tampered with. This solution can better prevent data from being tampered with.

Abstract: Implementations of the subject matter described herein provide methods and systems of controlling data backup, and a computer readable storage medium. The method comprises: obtaining test data for performing data backup with a plurality of backup solutions, the plurality of backup solutions being associated with each set of values amongst a plurality of sets of values of a plurality of factors affecting the data backup; generating a training sample set based on comparison of the test data; converting the training sample set into a decision model for controlling data backup; and optimizing the decision model based on the configuration parameters obtained by performing data backup with the decision model.

Abstract: According to example embodiments of the present disclosure, a method, an electronic device, and a computer program product for storage management are provided. The method includes: acquiring a lock attribute record in a lock attribute record chain from a data protection network for backing up data, a plurality of data protection servers of the data protection network reaching a consensus on the lock attribute record chain, the lock attribute record including a first attribute value of an attribute of a lock operation, the lock operation being used for preventing a backup of the data stored in a storage server from being tampered with; acquiring, based on the lock attribute record, a second attribute value of the attribute of the lock operation from the storage server; and generating, based on determining that the first attribute value does not match the second attribute value, an alarm indicating that the backup is tampered with. Thus, this solution can better prevent data from being tampered with.

Abstract: According to example embodiments of the present disclosure, a method, device and computer program product for data simulation are proposed. The method for data simulation includes: obtaining first data pattern information that is associated with a first set of operations executed on real data in a data protection system; generating, based on the first data pattern information, second data pattern information that is associated with a second set of operations executable by the data protection system; and generating, based on the second data pattern information, simulation data different from the real data, for the data protection system to execute the second set of operations on the simulation data. Thereby, the present solution can simulate efficiently and reliably a data pattern of real data, and thus generating simulation data of a data pattern similar to that of the real data.

Abstract: Implementations of the subject matter described herein provide methods and systems of controlling data backup, and a computer readable storage medium. The method comprises: obtaining test data for performing data backup with a plurality of backup solutions, the plurality of backup solutions being associated with each set of values amongst a plurality of sets of values of a plurality of factors affecting the data backup; generating a training sample set based on comparison of the test data; converting the training sample set into a decision model for controlling data backup; and optimizing the decision model based on the configuration parameters obtained by performing data backup with the decision model.