BenfordExplore how Benford’s Law can detect falsified data in text or images

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Open Source

Benford

Explore how Benford’s Law can detect falsified data in text or images

The Benford project provides a framework for using Benford's Law to determine if a given random data set has been modified.

Benford’s Law, also known as the Law of First Digits, the Phenomenon of Significant Digits, or the Law of Anomalous Numbers is the finding that the first digits (or numerals to be exact) of the numbers found in series of records of the most varied sources do not display a uniform distribution, but rather are arranged in such a way that the digit “1” is the most frequent, followed by “2”, “3”, and so in a successively decreasing manner down to “9”. The expected distributions can be seen in the screenshots below.

Essentially, when looking at a significantly large set of numbers, this law can tell you if the distributions of first digits follows Benford's Law. Deviations of significance should indicate data tampering. This can be applied in all kinds of use cases, from social likes and follower counts, to regional vote counts, financial information, and more.

This project has some sample images and voting data that you can use to see how Benford's Law applies to them.

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