Machine Learning and Artificial Intelligence advancements pave the way for typing-based authentication ervices like TypingDNA with high level of accuracy replacing other forms of biometrics.
What is DNA Typing?
DNA typing is a procedure wherein DNA extracted from a biological sample obtained from an individual is analyzed. The DNA is processed to generate a pattern for each person that is generally termed as a ‘ DNA profile’. This profile is unique for each person excepting that derived from identical twins.
TypingDNA use typing biometrics (also known as keystroke dynamics) to protect SaaS’s, web apps, eLearning(LMS), ePayments and devices.
How Does Typing Biometrics Work?
The way you type on your current keyboard is unique and suitable for information security enforcement.
TypingDNA records keystroke dynamics statistics about pressed keys of a user and turns them into typing patterns.
TypingDNA provides access to its typing-based authentication service through an API (application programming interface) and developers can add the functionality into their web apps through a software development kit.
API engine analyses and verifies the recorded typing patterns/keystroke patterns against previous patterns from the real owner.
The accuracy for matching such typing-based “fingerprints” to individual persons by using traditional statistical analysis and mathematical equations varies around 60 percent to 70 percent.
AI-powered typing pattern recognition technology has an accuracy of more than 99 percent and can even reach 99.9 percent when there is a sufficiently large typing profile built for the user over time.
More About Typing DNA :
Keystroke recognition is not meant to replace passwords or to be used alone as a method of authentication. Instead, it can be used in a multifactor authentication system and is easier to implement than other forms of biometric verification.
In order to build typing profiles, TypingDNA’s technology needs users to type a minimum of 60-70 characters.
Ultimately though, typing patterns are as vulnerable to cloning as other types of biometrics. Just as attackers can copy someone’s fingerprint, record their voice or obtain a high-resolution picture of their face, it is theoretically possible to record how someone types over a long period of time and then replicate that to defeat typing-based verification.
One common question that often comes up when discussing typing biometric technologies is how they handle various incidents that can affect the user’s style of typing. For example, when users are inebriated or experience dizziness, they’ll probably type slower and make more errors, which changes their typing profiles. Accidents can also temporarily leave users unable to type normally with one of their hands.
TypingDNA’s system is smart enough to figure out when a user continues to type normally on one half of the keyboard and differently on the other half, which suggests that they have a problem with one of their hands. A lower score on one half of the keyboard can be compensated by asking the user to type a longer text so that more data from the unaffected half is collected.
Typing pattern analysis can also have applications beyond authentication. TypingDNA is currently conducting research into the area of user profiling and has built an experimental system that attempts to determine a person’s gender, age, IQ, openness and personality (Myers–Briggs Type Indicator) based on how they type.
The large number of data breaches announced by online service providers over the past few years is a clear indication that password-based authentication is no longer enough. Two-factor authentication systems, often based on one-time-use codes sent via text messages or generated by mobile apps, have now become the norm.
But SMS is not a secure channel for transmitting authentication codes and users might not always have their mobile phones with them. AI-powered typing biometrics could be a viable alternative for the web, much more so than other forms of biometrics that require special access to peripheral devices.