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Malaysian experts: Why iPhone X’s Face ID may have just solved the ‘security friction’ problem

AvantiKumar | Sept. 25, 2017
Following Apple’s iPhone X reveal, Computerworld Malaysia asks CyberSecurity Malaysia, IDC, and three digital forensics investigators to probe security and privacy concerns raised by facial recognition systems.

Fong LGMS (new Aug17) -done

"Using Biometric lingo, facial recognition is less 'Intrusive' and less 'disruptive' when compared to other biometric technologies available now, such as voice recognition, fingerprint scanning, retina scanning, etc.," he said.

"Essentially, the effectiveness of biometric devices is measured by the likelihood of having false positives (errors)," he said. "It's rather challenging for facial recognition technologies to acquire a consistent high accuracy rate, especially if you compare it with other biometric devices like fingerprint or retinal scanners."

"Also, because of ageing and life styles, our facial appearance may change over time whereas our fingerprints and retina patterns will not have any change due to ageing," Chong said.

"The good news is that with the emergence and integration of today's advanced technologies -such as AI, artificial neural networks, and machine learning - facial recognition technology has now become more reliable and deliver consistent accuracy," he said. "For example, machine learning can help computers to 'predict' and 'anticipate' what we will look like when we age, or when we are wearing a spectacles or make-up."

"With the convergence of technologies, we can expect to witness the boom of biometric technologies in next the two years," Fong said.

Dr Amirudin agrees. "Face identify is now a universal and common data set, which allows rapid identification and verification. For facial recognition systems to work accurately, several poses are usually required to ensure all angles of a face is 'trained' by the system's machine learning algorithms (AI). In addition mobile biometrics applications, face ID is useful for public safety. The methodology is very useful in forensics and automatic detection of individuals blacklisted by authorities."

Reducing security friction?

Krishna Rajagopal expressed enthusiasm for Face ID to push facial recognition methodologies as a whole across sectors.  "The reason is simple. The fundamental challenge with multi factor / multi step authentication is that people 'feel' they have to do something 'extra' - to jump through some hurdles -to get to their messages, emails and photographs on their mobile devices: That's what we call as a security friction."

"I'm a personal advocate of keeping security simple," said Rajagopal. "So in the current scenario of the corporate world, most users have an uphill task, and that is tied in with password:

  • They're asked to come up with a secure, complicated password, with different combinations and special characters;
  • Users ponder and ponder and struggle to come up with a complicated password.
  • Users are then told to "change" that password every 90 days or so;
  • Then users are told that they can't use the previous passwords they have pondered for so long to come up with in the first place!
  • and users then resort to 'writing down' their passwords and often storing them in the most secure place in the world: Under the keyboard!"

 

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