A: The evaluation version of the software does not support files smaller than 500 Bytes or larger than 100 MB. Consequently, MinerEye Data Tracker™ may not catalog some especially small or large files. 

A: Yes, it is. You can view a graph of statistical information about your data and you can also download a CSV report of your tracked data according to the filters that you defined.

A: The number of clusters and their contained data are determined dynamically by the machine learning algorithm; It is not determined in advance or hardcoded. The top-level clusters should not be considered as a type of “categorization”, but rather as sets of data that include information that has a certain level of similarity. This concept also determines how lower level clusters are created.

A: After DataTracker scans your database, you will have two options for tagging your data: 

A. Provide the system with a sensitive file from your database (any file format you choose), and the system will display all the similar files sorted by their similarity to the original exemplar. 

B. You can explore your sensitive files according to entities, attributes and content and classify them by similarity. 

A: Tag and classification information are stored in the MinerEye Data Tracker™ OVA only. The actual data or files are not open for use by MinerEye Data Tracker™, or modified in any way. 

A: Similarity calculations are made using comprehensive deep learning algorithms proprietary to MinerEye Data Tracker™. A cluster’s similarity value can change over time as more files are added, changed or deleted. The algorithm cannot be modified, as it is designed and tested carefully to react only to the data content itself. 

AAs more files are added, it is likely that more clusters will be formed, and the files will be re-arranged more accurately.  

A: DataTracker compares the list of SHA1 in the data base to the list that has already been scanned. 

A: It is a vector of 1K created for each file no matter the format or size. It affects only MinerEyes’ OVA (Open Virtual Appliance). 

A: Our prerequisites are 8 core and 64 GB. 

Currently, we are not using GHz. Regarding threads, the more threads there are, the faster the scan will be. 

A: We pull out the signals and create groups by similarities.