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Are biometrics hack-proof?????

Biometrics usually refers to the process used to recognize, identify and authenticate persons based on certain physical or behavioral characteristics. Biometric verification is to identify a person uniquely by estimating one or more unique biological traits.
Now-a-days biometric authentication is also hacked which usually relies on factors like fingerprints and facial recognition. Some experts are worried that biometrics can be inherently weak because as they rely on some aspects that could change throughout a person's life.

We have come across generally recognition methods in our day2day life such as fingerprint, face recognition. These are few conventional methods which are used mostly for biometric applications.
Apart from the common Biometrics techniques, there are other Unconventional methods which are very rarely known.

“So, the Unconventional Biometrics will be the answer to the Hackers”


Types of Unconventional Biometrics:

1. Body Odour:

 Body odour of every person differs slightly, and this minute difference can be used to identify a person. Usually, a person’s body odour comprises of chemical compositions which can be analyzed, and the results are used to identify a person uniquely.
Animals have the extraordinary capability to recognize other animals by their scent. Where human ability falls short, machines are leveraged to fill the gap.  

Sensors are used for collecting the human scent sample data. The collected sample data is sent to odour biometric systems which in turn generates a unique template. Generated templates are stored in a biometric database which can be further used to verify the identity of the individual. Odour biometrics will not mask the actual body odour when external sources like perfumes and deodorants hinder them from misleading.

Application of Body Odour Biometric:
  • Security:  Used in the identification of terrorists and criminals without their knowledge.
  • Disaster management: Artificial or electronic nose can be used to identify the location of a person buried in debris and rescue.
  • This is used in tele-surgery, where the surgeons will need to identify certain smells.

2.                  Gait:

We can also recognize people who are familiar with their walking style, without looking at their face. This ability is a nature's gift to human brains; which can recognize a moving pattern, remember it and easily recall it. When this kind of ability is given to the computers it is called gait recognition system and the study is called gait biometrics.

Gait recognition system has the ability to map patterns of human gesture. It is also used to study animal locomotion. The mapped data is stored, and the gait biometric system can recognize the same pattern of motion by capturing and processing a new gait signature. It can use both video feed and sensor data to process and map pattern of an individual in motion. This Gait biometrics is mostly useful in individual identification in circumstances where other biometrics fail (i.e. in a moving crowd).

3.   Ear Recognition:

The shape of your ear is just as unique as the fingerprints. The unique shape of the lobe and curves that are different from person to person. This ear biometric methods are based on the processing of digital images of an ear. Still few methods are being improved in the ear recognition. To solve some crime cases in forensics ear prints are used. So, biometrics has come up with an app that can identify smartphone users in a way a person press their phone to their ear and cheek. 

4.  Lip Recognition:

Pattern made by the lip grooves provides a certain degree of uniqueness and that can be used to identify an individual. The lip patterns identification study is called Cheiloscopy. The Lip grooves patterns are significantly differing from person to person and that offers a vast prospect of variation. Lip prints are used in forensics for a long time for positive identification of a person. 

Biometrics are the new frontiers in Security so, find the advance Talks/Sessions at Artificial Intelligence and Neural Networks.

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