Openenf NPM | npm.io

Open ENF

Open ENF is an open-source Command Line tool to perform Electrical Network Frequency Analysis on an audio signal.

What is ENF?

Electrical Network Frequency Analysis is a forensic audio technique for validating audio recordings by comparing frequency changes in background hum with records of deviations in an electrical grid's standard operating frequency. Using ENF we can use the hum as a time-dependent digital watermark which can allow us to to timestamp recordings with single-second accuracy. For a more entertaining explanation Tom Scott does a nice explainer here:

When is ENF useful?

ENF Analysis can help you to:

Validate exactly when an audio recording was created
Detect if an audio recording has been edited or tampered with

ENF Analysis could be useful to you if you are:

A journalist
Involved in Open Source intelligence
A lawyer or a private investigator

Why OpenENF?

ENF Analysis has been around for at least a decade but no open-source solution has existed. The lack of open source code limits access to the technique to just law enforcement agencies and a handful of specialist forensic audio firms. The Open ENF project aims to broaden this access to journalists, open source intelligence specialists and others.

Additionally, the lack of an open source ENF method limits it's application in a courtroom setting as potential errors in closed-source analysis are hard to identify and impossible to effectively cross-examine.

Installation

Open ENF is a cross-platform command-line tool, distributed via NPM:

> npm install --global openenf

Usage

Fire up a terminal and do this:

> enf /path/to/a/wav/file.wav

The first time you perform an an analysis enf will download grid frequency data. (At the time of writing this is only for the Central European and Great British grids but we're working on getting it working for more locations.)

> Downloading Grid Frequency Data |███████████████████████████████████░|99% || Downloading DE.freqdb

After the grid data is downloaded the CLI starts analyzing the audio...

> ENF Analysis |████████████████████████████░░░░░░░░░░░░| 70% || Comparing frequencies to grid data...

...and finally returns a result:

ENF Analysis |████████████████████████████████████████| 100% || ENF analysis complete.
Match found.
Best guess for when this audio was recorded:
Tue Apr 25 2017 12:14:08 UTC
Score: 0.74344023323615
Grid: DE

For this example, the best estimate for when this recording was made was 25th April 2017 at 13:14 on the DE (Central European) grid. It has a score of less than 1 which indicates a very strong match (see Scoring below for a fuller explanation of the score)

CLI Options

ENF Analysis is very processor-intensive but we can speed up analysis times by specifying:

The time period over which we search for a match
The electrical grids we match against

As an exmaple, if you know your recording was made in Great Britain sometime between April and June 2020 you can speed things up a lot by specifying these parameters in the command line:

> enf /path/to/a/wav/file.wav --grids GB --start 2020-04-01 --end 2020-06-30

The CLI options currently available:

--grids The electrical grids you want to search, currently either GB, the Great British grid (excluding Northern Ireland) or DE, the Central European Grid which covers the majority of countries in Europe.
--start The time you want to start searching from. Any Javascript-parseable date will work here.
--end The time you want to search up to.

Limitations

ENF Analysis does not always return a result. The enf CLI tool will fail to return a result if:

The recording was made far away from an electrical hum source (i.e. the majority of exterior recordings)
The grid frequency is 60HZ (for example if the recording was made in North America)
The recording is too short (typically for a good match a recording needs to be at least 3 minutes)
The recording is noisy (i.e. if there are other sources of low frequency audio, like traffic or music, on the recording)
The recording was made before January 2010, which is the earliest time for which we have grid frequency information.

Additionally, and especially for short recordings, you may get a result with a low score. These can be difficult to interpret. See Scoring below:

Audio formats

At present OpenENF can only handle .wav files. An integration with FFMPEG is in the works but until that's been implemented a number of tools exist (for example Audacity) that can help you convert between formats.

Scoring

Open ENF should currently be considered beta software and we shouldn't regard results as 100% reliable. One of the Open Questions (below) is how we can return more meaningful results from an analysis. For now, a result is assigned a single numerical score. A score close to zero indicates a stronger match. You can broadly interpret scores as follows:

Less than 1 indicates a strong match, especially for a recording of at least 15 minutes duration.
1 to 15 indicates a potential match, especially for a recording greater than 15 minutes duration.
Greater than 15 indicates that a match was found, but there's a strong likelihood that this match was just chance. Don't take results like this too seriously.

Open Questions

There exist a number of questions, the answers to which we greatly improve the usefulness of the tool:

More Meaningful Scores

It would be great to return a score which gives the liklihood of a match compared to chance, similar to a forensic DNA result. In other words, the tool would return a result which said something like:

"There is 98% chance that this recording was made on 15th August 2017 at 20:15:03"

More Grid coverage

At present we can only locate publicly available grid data for:

The Central European grid.
The Great British grid
The Nordic area (i.e. Iceland, Norway, Sweden and Finland)
The Ireland grid (which covers both the Republic and Northern Ireland)

Of these, the Central European and Great British grids are integrated into the tool, and the Nordic and Irish grids are expected to follow shortly. However, Open ENF still only works in Europe. Obtaining North America, Chinese and Russian grid frequency data would greatly extend the use of Open ENF but public data for these regions is currently unavailable. Indeed, for some regions it seems unlikely that grid frequency data will ever be publicly available.

It's possible to record grid frequency data and upload it to the internet using a smartphone. This technique would allow us to obtain grid data from areas where no official source exists. If you are an open-source intelligence analyst who could help to contribute to a grid frequency database we would love to hear from you, especially if you're outside of Europe.

Contributing

Contributions are most welcome. Technical documentation and a CONTRIBUTING.MD are works in progress but here's bullet-pointed overview of the structure of the project:

The tool is an NPM Command Line tool
The analysis phase is written in Typescript and uses an adaptive Goertzel algorithm to obtain low-frequency audio data
The lookup phase is written in .Net Core C# and communicates with the Command Line tool over TCP
Unit tests can be run locally with npm test for Typescript and an XUnit test runner within C#
The integration pipeline runs both the Typescript and C# tests suites for each PR. All tests need to pass before a PR can be considered for approval.

License

The code for Open ENF is licensed under GPLv3 . The grid frequency data used for lookups is explicitly excluded from this license and is not included in the repository.

Funding

Open ENF has is free and available for anyone to use. It also represents hundreds of hours of development time. We hope to continue to develop Open ENF so we can more accurately authenticate audio for more territories, and we're currently seeking funding to help us do that. If ENF is useful to you please consider a regular or a one-off contribution to help move the project forward. In exchange for funding we can give you early access to new releases and new grid data in all territories as soon as it becomes available. If you'd like to help fund this project and help us grow please get in touch.