The insight of FaceGuard is humans reliably recognize familiar faces in a crowd of strangers. An emotional connection – positive or negative – assures recall. So how does a FaceChallenge work and what creates the security?

FaceGuard begins with an initial set of 400 “Core” faces provided with the app.  They are not accessible but can be “updated” with 100 replacing 100 each quarter. The unknown images are used as part of the random background. The four hundred (400) crowd faces are balanced to reflect the current population of the United States. Accordingly, the correct percentage of each ethnicity, age range, and gender are included in the base. Just like in real life, any given FaceChallenge may display a mix appearing unbalanced, but in total, FaceChallenges are proportional.

There are five (5) possible FaceChallenges the user may assign:
A) Blank – no FaceChallenge
B) 1 known face in a 3×3 panel of 9 faces
C) 1 known face in a 3×3 panel of 9 faces – 5 panels – so 5 known faces within 45
D) 2 known faces in a 4×4 panel of 16 faces – 2 panels – so 4 known faces within 32
E) 3 known faces in a 4×6 panel of 24 faces – 3 panels – so 9 known faces within 72

The formula employed:  n!/[(n-r)!r!]   The odds against unauthorized access are:
A) 0 – use for Destinations with no restricted access nor sensitivity (Wikepedia)
B) 1 in 9 – convenient for required log-in – discourages children and casual access
C) 1 in 59,049 stops snooping – easy for the user but seriously difficult to breach
D) 1 in 14,400 – primarily a FaceChallenge style preference – formidable protection 
E) 1 in 8,291,469,834 – secures medical, financial, legal and similar activity.


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