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Insights into TypingDNA typing patterns and the type-to-output tool

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What are typing patterns?

Typing patterns are the digital representation of a person’s unique typing behavior, similar to physical biometrics such as fingerprint recognition, facial recognition, and iris scanning. 

To generate a typing pattern, TypingDNA uses an array of different metrics, including press time, which is the duration that a key is pressed, and seek time, which is the duration between keystrokes. When people type on their keyboards, TypingDNA develops a string of parameters that determine individual attributes of the way they type. 

What are TypingDNA recorders?

Whenever you implement TypingDNA, you should start by integrating our typing pattern recorders. Make sure to go to TypingDNA’s GitHub repository and download the latest version of the recorder that works best for the technology you are using. 

Direct links:

Take a look at this tutorial we’ve made to find out how to record good typing patterns.

What forms a typing pattern?

Any typing pattern has a header and a body. The header is crucial for the accurate interpretation of the information found in the body of the typing pattern, which defines the way the user types. Type 1 & 2 (more information below) patterns share a similar structure:

The header of a typing pattern consists of general information, including device type, recorder version, text length, operating system, browser type, browser version, and browser language. It also includes text ID, ahashed value obtained from the data typed by the user used to verify whether they have previously saved other typing patterns for the same text without knowing what the user has actually typed.

The body of the typing pattern allows us to go into more detail about how the user types: the time between two keypresses, how long they hold a key down, keyboard input (whether the keyboard is touch-based, physical, or a combination of both), and keyboard type (internal, external, or mixed).

Find out more in the API documentation.

How does a typing pattern differ on mobile?

For mobile, typing patterns also include data gathered on each keypress from the gyroscope and accelerometer, including acceleration, rotation, pitch, and roll, all of which help increase…

Source…

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SwiftKey’s typing predictions may have leaked users’ emails

SwiftKey, a popular keyboard app, has suspended a syncing feature that may have leaked users’ emails to strangers.

The problem has been popping up through the app’s prediction bar. A few users on Reddit have noticed that it’s been offering strange suggestions — including emails they’ve never seen and foreign language terms they’ve never used.

“And now, I’m getting someone else’s German predictions,” wrote one user, who recently rooted a Samsung Galaxy S6 phone. “I have never typed German in my entire life.”

The problem might be related to how SwiftKey collects data on the words and phrases users type. That data is then analyzed and used to predict the customer’s typing habits, including what emails they tend to enter — only in this case those predictions are possibly being shared to others.  

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