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. 2013 Dec 19;7:835. doi: 10.3389/fnhum.2013.00835

Table 1.

Summary of salient typing demand, analysis mode, and accuracy rates for a spectrum of different keystroke biometric approaches.

Typing input demand Method of analysis Accuracy Reference
10 character string input 10 times with 30 participants Statistical (χ and ρ) FAR = 1.89% Araújo et al. (2005)
FRR = 1.45%
Circa 40 character string input 10 times with 100 participants Statistical (GPD fused with DSM) EER ≈ 1% Teh et al. (2011)
Circa 30 character string input 10 times with eight participants Statistical (GMM) FAR = 2.1%; FRR = 2.4%EER < 3% Hosseinzadeh et al. (2006)
Short phrase entry with six participants Artificial Neural Net Accuracy = 97.8% Obaidat and Macchairolo (1993)
15 valid and 15 invalid users × 225 sequence ANN + Fuzzy logic EER = 0% Obaidat and Sadoun (1997)
Short password entered three times with 90 valid and 61 imposter participants Multilayer back propagated ANN FAR = 1.1%; FRR = 0%* Lin (1997)
7 character string input between 150 and 400 times with 25 participants ANN using multilayer perceptron FAR = 0%; FRR = 1% Cho et al. (2000)
At least 8 character string input 25 times with 29 participants to study Fuzzy logic FAR = 2.79%; FRR = 7.379% De Ru and Eloff (1997)
683 character string using 154 participants Statistical - trigraph-based FRR = 4%; FAR = 0.01% Bergadano et al. (2002)
Short (n < 15 characters) strings input 10 times with 23 participants Auto-regressive classifier linked to pressure data EER ≈ 3% Eltahir et al. (2008)
10 character password input to database enrolment with 50 samples (30 genuine and 20 forged) Statistical; & Statistical augmented with pressure data EER = 2.04%; EER = 1.41% (P-augmented) Lv and Wang (2006)
8 character string with 10 timing- and 10 pressure vectors recorded Artificial Neural Net augmented with pressure data EER values of 16.5, 14.94, and 11.78% for respectively, pressure, latency, and pressure + latency Loy et al. (2007)
Short string pairs input 15 times with 20 participants Independent component analysis and fast-ANN augmented with acoustic record FAR = 4.12%; FRR = 5.55% Nguyen et al. (2010)
*

With refined thresholding.