Thesis - Instituto de Telecomunicações

138 CHAPTER 7. CONCLUSIONSTable 7.1: Comparison between various behavioral biometric techniques.Technique EER Pros ConsVoice Dynamics [193] ∼ 5% easy to collect sensitive to noise andvoice alterations; simpleto circumvent withrecorded voiceKeystroke Dynamics [164] ∼ 4% non-intrusive method keystrokes can be replayedSignature Dynamics [253] ∼ 2% difficult to spoof requires additionalhardwarePointer Dynamicssimple addon to otherpoor performance for10 strokes ∼ 10% security systems, lowshort interaction20 strokes ∼ 5% intrusion and hard toperiods30 strokes ∼ 2% reproduceHeart Dynamics difficult to spoof intrusive technique20 beats ∼ 5%50 beats ∼ 3%100 beats ∼ 2%We studied the heart dynamics biometric trait and identified usage possibilities similarto the pointer dynamics trait, with the drawback of being a highly intrusive system.The sympathetic dynamics trait provided a signal with similar characteristics among theusers, but we devised techniques to use discriminative information from a poorly separabledata source. This approach led to a simple integration of soft biometric traits in a fusionwith improved performance.Table 7.1 compares some behavioral biometric techniques with the proposed behavioraltechniques (pointer and heart) for different sequence duration lengths.The EDA based technique has a lower discriminative value, only being useful in multimodalenvironments. Given the performance of the proposed biometric techniques, thereare situations when only a short period of time is available for signal collection. In thesesituations, the technique can only be considered as a soft-biometric trait. When the systemcan be structured for longer interaction periods the system presents similar performancesto other standard behavioral biometrics systems.With the present work we provide a strong basis to support that soft-biometrics can be