Unique FingerPrint ID (UFPID)

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Last update: 15-11-2023

The Smart DAQ has onboard a cryptographic integrated circuit, the ATSHA204. This IC utilizes an SHA-256 Hash Algorithm and has a Unique 72-bit Serial Number that is utilized for the identification of the smart device on an experimental setup, and later when performing experimental data origins validation tasks.

This is necessary so any sensor data measurements made with this smart DAQ can be traced back to its origins in the laboratory where experimental testing was made, combined with a Unique 72-bit Serial Number. This kind of experimental data validation is unique to each experimental data measurement made and uploaded to any data repository, for instance, a dataverse. See here for more detailed information about this IC.

Universal Numerical Fingerprint [1]

The Universal Numerical Fingerprint (UNF) is a unique signature of the semantic content of a digital object. It is not simply a checksum of a binary data file. Instead, the UNF algorithm approximates and normalizes the data stored within. A cryptographic hash of that normalized (or canonicalized) representation is then computed. The signature is thus independent of the storage format. E.g., the same data object stored in, say, SPSS and Stata, will have the same UNF.

UNF version 5, on which current version 6 is based, was originally described in Dr. Micah Altman’s paper “A Fingerprint Method for Verification of Scientific Data”, Springer Verlag, 2008. The reader is encouraged to consult it for an explanation of the theory behind UNF.

More detailed information can be found on the dataverse.org website here.

An artificial” list of sample UNFs of various data types is provided with the source of the UNF v6 Java implementation.

Custom Implementation of a UNF

Dataverse's UNF is a step forward in the Verification of Scientific Data, however, additional verification is required for the data measurements themselves. In particular, the actual data origins from a specific Data Acquisition Device where measurements are collected and transformed into an experimental data record.

The Unique FingerPrint ID (UFPID) hash string generated on the proposed Smart DAQ utilizes the following data:

• Local Date & Time [1];
• Start Time [1];
• Elapsed Time [1];
• sensor data array [1...n];
• onboard temperature [1];
• onboard humidity [1];
• MCU temperature [1];
• onboard motion vector [x, y, z];
• onboard yaw vector [x, y, z];
• Geo-location data (external IP address and geo-location coordinate resolution from an external public website)

To the sensor data measurements collected at any given point in time, during an experiment, are also added:

• two environment data values, characteristic of the environment where the experiment is running. The onboard Temperature and Onboard Humidity;
• Geo Location data obtained from IP Geo tracing from the internet. The Latitude, Longitude, and also the time of request for Geo-Location data;
• The Unique 72-bit Serial Number of the smart DAQ itself;
• an onboard motion vector [x, y, z];
• and an onboard yaw vector [x, y, z];

This additional data string added to the experimental data hashed to generate a UNF enables linkage to the smart DAQ device with the experimental data record by adding specific environmental time-dependent data, varying over time during an experiment, reducing even further the possibility of data forgery. Furthermore, it is included information about the motion/displacement of the smart DAQ itself, which can be utilized for verification of unwanted handling when the experiment is left unattended in a laboratory.

References and Sources

[1] www.dataverse.org