International Business Machines Corporation

M Corneliu Constantinescu

Wayne A Sawdon

Frank Bernhard Schmuck

Leo Shyh-Wei Luan

Marc Adam Kaplan

Sven Oehme

Leo S Luan

Gero Friedrich Wolf Schmidt

Deepavali M Bhagwat

A computer-implemented method includes monitoring file access activity and generating an audit log based on the file access activity. The method also includes collecting samples of file usage activity, running a pattern recognition algorithm on the samples of the file usage activity for detecting malware activity, and, in response to detecting malware activity, restoring at least one file based on the audit log. A computer program product includes one or more computer readable storage media and program instructions collectively stored on the one or more computer readable storage media. The program instructions include program instructions to perform the foregoing method. A system includes a processor and logic integrated with the processor, executable by the processor, or integrated with and executable by the processor. The logic is configured to perform the foregoing method.

Detection of encrypting malware attacks

Embodiments relate to policy-based, multi-scheme data reduction for a computer memory. An aspect includes receiving a plurality of policy rules by a policy engine of the computer memory, wherein a first policy rule specifies applying a first data reduction scheme to data in the computer memory based on the data matching first characteristics, wherein a second policy rule specifies applying a second data reduction scheme to data in the computer memory based on the data matching second characteristics, wherein the first data reduction scheme is different from the second data reduction scheme. Another aspect includes determining, by the policy engine, that first data in the computer memory matches the first characteristics, and that second data in the computer memory matches the second characteristics. Yet another aspect includes applying the first data reduction scheme to the first data, and applying the second data reduction scheme to the second data.

Policy-based, multi-scheme data reduction for computer memory

The embodiments described herein relate to managing compressed data to optimize file compression. A compression is performed on a first set of data to create a first set of compressed data partitions in a compression group. A partition table is constructed, and partition entries for the first data block are added to the table in conjunction with the first set. A current size of the compression group is assessed. In response to a compression ratio being greater than a target compression ratio and internal fragmentation of the compression group being smaller than a threshold, the compression group is dynamically completed. The dynamic completion decides a size for the compression group. The partition table is added to the compression group by assigning space within the first compression group for the table. The compression group is written to persistent storage.

Compressed data layout with variable group size

The embodiments described herein relate to managing compressed data to optimize file compression. A first compression is performed on a first set of data to create first compressed data. The first compressed data is stored in one or more blocks of a first compression group. A size of free space of a last block of the first compression group is discovered and calculated. A second compression is performed on a second set of data to create second compressed data. At least a portion of the second compressed data is supplied to the first compression group for padding into the last block in response to determining that the size of the free space is sufficient. An unpadded portion of the second compressed data is stored in one or more blocks of a second compression group.

Compressed data rearrangement to optimize file compression

A computer-implemented method according to one embodiment includes dividing data into a plurality of partitions, creating a plurality of groups of different data types within each of the plurality of partitions, independently compressing, within each of the plurality of partitions, each of the plurality of groups of different data types to create a plurality of independently compressed partitions, and validating each of the plurality of independently compressed partitions to create a plurality of validated independently compressed partitions.

Managing compression and storage of genomic data

A computer-implemented method according to one embodiment includes identifying genomic data within a system, dividing the genomic data into a plurality of partitions, creating a plurality of groups of different data types within each of the plurality of partitions, independently compressing, within each of the plurality of partitions, each of the plurality of groups of different data types to create a plurality of independently compressed partitions, validating each of the plurality of independently compressed partitions to create a plurality of validated independently compressed partitions, and saving the plurality of validated independently compressed partitions within the system.

The embodiments described herein relate to managing compressed data to optimize file compression for efficient random access to the data. A first partition of a first data block of a compression group is compressed. The first compressed partition is stored in a first compression entity. An in-memory table is maintained, which includes updating the in-memory table with data associated with an address of the stored compressed first partition. At such time as it is determined that the first compression entity is full, the in-memory table is compressed and written to the first compression entity. Accordingly, the in-memory table, which stores partition compression data, is store with the compression entity.

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San Jose, CA, United States of America

M Corneliu Constantinescu