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Analysis of the Global Mobile Biometrics Market

  • August 2014
  • -
  • Frost & Sullivan
  • -
  • 50 pages

Summary

Table of Contents

End Users Will Drive the Widespread Adoption of Mobile Biometric Authentication

In 2013, Apple and Samsung have revealed mobile devices with biometric features embedded. Samsung has decided to follow the same strategy as Apple by including fingerprint sensors in order to access the mobile handset. Samsung, in that case, has been seen as a follower rather than a leader. Indeed, instead to use innovative approach such as iris recognition, the firm has decided to use the same biometric technology than Apple. Is there an opportunity for biometric features to become an alternative for 2FA or strong authentication? This research service covers hot topics regarding biometric on mobile, does market trend and threat analysis, and gives revenue forecasts for the mobile industry.

Key Findings
-Biometric research and development has reached maturity. The number of published patents has been decreasing since 2008. The next step is to have an approved biometric application relevant for mobile and widespread deployment.
-According to Frost & Sullivan, fingerprint and voice recognition are the most interesting biometric technologies that the mobile industry should focus on.
-In order to facilitate more secure applications, multimodal authentication will also gain popularity.
-Biometric revenue from smartphone security products will only have a % compound annual growth rate. Fingerprint sensors will support the growth during the same period. In 2019, Frost & Sullivan expects the market to generate € million based on hardware and software embedded.
-New products to be launched in 2016–2017 will support market growth. In the same period, there will be a transition from the early adopter trend to the early majority. The number of biometrics smartphone users will reach million in 2017. Between 2013 and 2019, the compound annual growth rate will reach %.
-Frost & Sullivan has identified several opportunities for biometric technology in mobile, such as payment, mobile commerce, social media, and for usages that required stronger security mechanisms.

Key Definitions—Biometric
-Fingerprint recognition is the method of identification using the impressions made by the minute ridge formations or patterns found on the fingertips.
-Palmprint recognition is a technology that uses palmprint features, which are composed of principal lines, wrinkles, minutiae, and delta points. These features are captured as images and used for identification.
-Iris recognition is a technology based on a black-and-white image of eye captured using IR video camera to be compared with various parameters, such as rings, furrows, and freckles in the cornea, iris, and pupil of the eye.
-Face recognition uses facial characteristics (distance between eyes, width of nose, depth of eye sockets, mouth, jaw, and cheekbones) to map the nodal point on an individual’s face and compares these characteristics with a stored image in the database.
-Voice recognition involves authenticating a speaker based on numerous voice characteristics, such as vocal tract geometry, harmonics, pitch, and range.
-Multimodal recognition involves using more than one biometric variable, such as fingerprint, voice, face, or iris, to authenticate the user. This approach allows for better matching during the authentication process.

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