Hitoshi Kokumai

3年前 · 2 分の読書時間 · ~10 ·

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On Ruinous Misperception of Biometrics

On Ruinous Misperception of Biometrics

FRR (F alm Rejection Rass)

 

False Acceptance Rates and False Rejection Rates

 

 

10

104

104

    
   

3% (Equa Error Rates)

10%

10°

  
 

procuct®
(more accurate)

 
 

FE EE ET)
FAR (Fate Accegtance Rates)


Here are some of my recent writings about the misperception on security-ruining biometrics.


‘Not as secure as claimed’ is one thing. ‘Harmful to security’ is another.


If Only It Were True


Probabilistic Is Human Body, Not Pattern-Matching Algorithm


US Army appears tobe scarily misguided


Finger vein technology


AI-Enhanced Biometrics – How Dreadful?


7d38a0e7.png


Quantitative Examination of Multiple Authenticator Deployment

It appears that there are so many security professionals who pay no attention to the exactly opposite effects of 'multi-layer' and 'multi-entrance deployments. ‘Multi-Layer’ is also represented by ‘In-Series’, ‘In-Addition-To’, ‘All/BothAnd’ and ‘Conjunction’ in logic, while ‘Multi-Entrance’ by ‘In-Parallel’, ‘In-Stead-Of’, ‘EitherOr’ and ‘Disjunction’. Let me offer a quantitative examination of multiple authenticators deployed in two different ways.

Vulnerability (attack surface) of an authenticator is generally presented as a figure between 0 and 1. The larger the figure is, the larger the attack surface is, i.e., the more vulnerable. Assume, for instance, as just a thought experiment, that the vulnerability of the PKI-enabled token (x) be 1/10,000 and that of the password (y) be 10 times more vulnerable, say. 1/1,000. When the two are deployed in ‘multi-layer’ method, the total vulnerability (attack surface) is the product of the two, say, (x) and (y) multiplied. The figure of 1/10,000,000 means it is 1,000 times more secure than (x) alone.

On the other hand, when the two are authenticators deployed in ‘multi-entrance’ method, the total vulnerability (attack surface) is obtained by (x) + (y) – (xy), approximately 0.0011. It is about 11 times less secure than (x) alone.

So long as the figures are below 1, whatever figures are given to (x) and (y), deployment of 2 authenticators in ‘multi-layer’ method brings higher security while ‘multi-entrance’ deployment brings lower security. As such ‘multi-layer’ and ‘multi-entrance’ must be distinctly separated when talking about security effects of multiple authenticators.

Remark: Some people may wonder why (xy) is deducted from the sum of (x)+(y).

When (x) and (y) is very small, the (xy) is very close to 0, which we can practically ignore. But we should not ignore it when the figures are considerably large.

Suppose a case that both the two authenticators are deployed in an extremely careless manner, for instance, that the attack surfaces of (x) and (y) reach 70% (0.7) and 60% (0.6) respectively. If simply added the figure would be 130% (1.3). It conflicts with the starting proposition the figures being between 0 and 1.

Imagine a white surface area. Painting 70% of it in black leaves 30% white surface. Painting 60% of the remaining 30% in black will result in 88% black and 12% white surfaces. Painting 60% first in black and then painting 70% of the remaining 40% brings the same result of 88% black and 12% white. So does “(x)+(y)­-(xy)”. The overall vulnerability (attack surface) is 0.88 (88%) in this case.

The same calculation applies to biometrics used in cyber space where it has to rely on a fallback password/PIN deployed in ‘multi-entrance’ method against false rejection. You might assume that biometrics deployed with a password/PIN in ‘multi-layer’ method should bring us a very high security. But, very sadly, this scenario never comes true. When rejected by biometrics, what can we do? We will only see that we are unable to login even if we can feed our password/PIN.

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