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What are 'Behaviometrics'?

Behaviometrics – More Secure than Fingerprints?





Behaviometrics” is a portmanteau of behavioural and biometrics – technologies and methods used to measure and analyse. Behavioural characteristics is the term used to refer to the manner in which we interact with the world around us – how we walk, sit, type etc. Physiological traits (fingerprints, facial images, eye characteristics) have formed the basis of biometric security measures.

Behaviometrics is the next step in ID verification, measuring how we move based on our physiology to recognize and verify the individual. Not just how we walk or sit but also how we talk, the vocabulary that we use, can distinguish us and are thus viable identification markers.

Individual differences are also found in the way in which we interact with physical devices – smartphones, tablets, keyboards, touch screens and peripheral devices (such as a mouse). Again, these traits can be used to authenticate the individual.

Behaviometrics can add a much needed additional layer of security in the fight against cybercrooks – eventually we will be able take advantage of advances in AI to create multi-factor authentication that encompasses traits such as facial muscle motion or the manner in which we hold the device that we use to enter our login details. Behaviometrics will create an adaptive security net that routinely updates itself based upon user behaviour.

Increased online economic activity has lead to greater criminal efforts in the cyber-sphere. This increase in legitimate use has been matched (if not superseded by) the growth in the criminal utilization of online opportunities.

Growing sophistication in methods of identity theft have caused financial institutions and government bodies to improve security relating to personal data. Multi-factor authentication is now the absolute bare minimum level of security used by organizations that claim to be security conscious.


What is Multi-factor authentication?

MFA is the practice of sending a code to a known device or an email to an address associated with the individual. This approach combines authentication of something a person knows like a password with something they own, a mobile device.

One of the main weaknesses of this system of MFA is that the token may be accessible on the same mobile device being used to access the account.

Behaviometrics could be the next step in cyber security, a viable tool to address the current gaps in today’s security measures. The question now is whether it has reached a level of maturity where it can be broadly adopted?


Studies in Behaviometrics:

Identify users by their footsteps

...a system for identifying people based on their footstep force profiles and have tested its accuracy against a large pool of footstep data. This floor system may be used to identify users transparently in their everyday living and working environments. We have created user footstep models based on footstep profile features and have been able to achieve a recognition rate of 93%.”



Behaviometrics for Identifying Smart Home Residents http://www.eecs.wsu.edu/~cook/pubs/haai13.pdf:

By using behaviometrics-based approaches, the smart home may identify residents without requiring them to carry a tracking device, nor use privacy insensitive recording systems such as cameras and microphones. With the ability to identify the residents through behavior, the smart home may better react to the multitude of inhabitants in the space.”


Downside?

The accuracy of the profiling eradicates any current privacy methods - it renders TOR and VPNs useless. Third parties could find means of linking behaviometrics to individual users. Users would need to find tools/plugins that will obscure their identity.

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