Cybersecurity has historically relied on credentials. These credentials act as confirmations of an individual’s identity and are indirectly related to the individual. The most popular credential that websites require is a simple password.
However, rising numbers of hackers that steal information for financial gain (so-called black-hat hackers) mean that indirect identity credentials are less and less secure. Your password could be taken with relative ease by keylogging, data-breaches or even by monitoring all data sent over WiFi. Many of these attacks target individuals that the hacker does not know personally so, in response to credential hacks, companies have started using identify-verification techniques relying on the most directly personal identification you can provide: your face. This is especially useful for companies that have obligations to verify identity under Know Your Customer (KYC) compliance rules. These rules can be complex, but are an important protective procedure against fraud, corruption and even terrorism. All businesses are encouraged to spend some time learning about KYC compliance obligations, as they serve an important function in our cyber society.
Facial recognition eliminates the need for users to recall as many as 30 passwords, and eliminates the need for cybersecurity mechanisms to rely on a certification as impersonal as a password. It is the most promising of AI biometric techniques, which are verification techniques that make use of Artificial Intelligence’s ability to deep learn.
Deep learning is a type of machine learning that trains a computer to perform tasks that previously were only able to be done by humans. Recognising speech, identifying images and much more can be achieved by setting up data parameters and training a computer to learn on its own with many layers of processing capabilities.
Other promising candidates in the biometric sphere of cybersecurity include voice recognition, fingerprint scanning, iris recognition and behavioural biometrics. All biometrics validate the individual as opposed to a credential. Behavioural biometrics has sparked much interest as does not require explicit authentication from the user; it instead validates based on behaviour such as how the user moves a mouse, types or presses a touch screen. It is almost impossible to imitate a typing or pressing pattern purposefully, though black-hats no doubt will find a way eventually. However, for immediate transactions and identity verification, facial recognition is proving itself as the future of cybersecurity.
This is partly because identity checks have long been the same: present a document that verifies a government’s confirmation that your name belongs to the individual with your face; have the person validating your identity hold it up next to your face to check if they belong to the same person; have your identity confirmed or rejected.
This is what AI helps to do, just at much, much greater speeds than a human would be capable of doing. It means that cybersecurity solutions that facilitate KYC compliance don’t need to rely on tens or hundreds of employees who have the job of comparing faces all day. Having a computer doing repetitive and boring jobs instead of humans increases the whole of society’s efficiency, as machines do not suffer from harmful employee burnout.
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