Why face recognition is the future of cybersecurity?
https://newsstechh.blogspot.com/2019/10/why-face-recognition-is-future-of.html
Why face recognition is the future of cybersecurity?
Cybersecurity has historically worked on the principle of recognizing credentials. These credentials act as assertions of an individual's identity and are indirectly related to the individual. The most popular credentials required from websites are a simple password.
However, an increasing number of hackers who steal information for financial gain can take your password relatively easily by writing down keys or data breaches or even by monitoring all data sent over WiFi.
Many of these attacks target individuals who the hacker doesn't know personally. Companies have begun to use identity verification methods based on the most obvious personal identity you can provide: it's your face.
This procedure is especially useful for companies with identity verification obligations under the KYC compliance rules. These rules may be complex, but they are an important preventive measure against fraud, corruption and even terrorism. All companies are encouraged to spend time learning about their KYC compliance obligations, as they serve an important function in our online community.
Face recognition eliminates the need for users to recall up to 30 passwords and eliminates the need for cybersecurity mechanisms to rely on an impersonal certificate such as a password. It is the most promising biotechnology in AI, which is verification techniques that use AI's deep learning ability.
Deep learning is a type of machine learning that trains a computer to perform tasks that previously could not be performed by humans. Speech recognition, image identification and 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 field of cybersecurity include voice recognition, fingerprint scanning, iris recognition and behavioral biometrics.
Behavioral biometrics have aroused a lot of attention because they do not require explicit user authentication; instead, identity validation is based on behavior such as how the user moves the mouse, writes or touches the touch screen. It is almost impossible to mimic the pattern of writing or pressing purposefully. For instant transactions and identity verification, face recognition proves to be the future of cybersecurity.
This means that cybersecurity solutions that facilitate compliance with KYC rules do not need to rely on dozens or hundreds of employees who have the task of comparing faces throughout the day. Having a computer that performs repetitive and tedious jobs instead of humans increases the efficiency of society as a whole, as machines do not suffer from the harmful fatigue of employees.
Cybersecurity has historically worked on the principle of recognizing credentials. These credentials act as assertions of an individual's identity and are indirectly related to the individual. The most popular credentials required from websites are a simple password.
However, an increasing number of hackers who steal information for financial gain can take your password relatively easily by writing down keys or data breaches or even by monitoring all data sent over WiFi.
Many of these attacks target individuals who the hacker doesn't know personally. Companies have begun to use identity verification methods based on the most obvious personal identity you can provide: it's your face.
This procedure is especially useful for companies with identity verification obligations under the KYC compliance rules. These rules may be complex, but they are an important preventive measure against fraud, corruption and even terrorism. All companies are encouraged to spend time learning about their KYC compliance obligations, as they serve an important function in our online community.
Face recognition eliminates the need for users to recall up to 30 passwords and eliminates the need for cybersecurity mechanisms to rely on an impersonal certificate such as a password. It is the most promising biotechnology in AI, which is verification techniques that use AI's deep learning ability.
Deep learning is a type of machine learning that trains a computer to perform tasks that previously could not be performed by humans. Speech recognition, image identification and 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 field of cybersecurity include voice recognition, fingerprint scanning, iris recognition and behavioral biometrics.
Behavioral biometrics have aroused a lot of attention because they do not require explicit user authentication; instead, identity validation is based on behavior such as how the user moves the mouse, writes or touches the touch screen. It is almost impossible to mimic the pattern of writing or pressing purposefully. For instant transactions and identity verification, face recognition proves to be the future of cybersecurity.
This means that cybersecurity solutions that facilitate compliance with KYC rules do not need to rely on dozens or hundreds of employees who have the task of comparing faces throughout the day. Having a computer that performs repetitive and tedious jobs instead of humans increases the efficiency of society as a whole, as machines do not suffer from the harmful fatigue of employees.
