# The Impact of Pressure on the Fingerprint Impression: Presentation Attack Detection Scheme
## 4 Experiment Setup
### The Database  
The presented database consists of two portions: (1) dynamic presentations with ordinary presentations. This portion was introduced in our previous works [22; 23] to analyze the dynamic fingerprint pattern in the typical use case; (2) Dynamic presentations where the capture subject applies additional pressure during the presentation. The latter portion is collected seeking to extend the state-of-the-art (SoA) investigations on dynamic fingerprint features, also to study the fingerprint's dynamic-reaction to pressure. The complete database (Table 3) consists of 7128 fingerprint videos that correspond to bona fide and attack presentations. The data were collected from 66 statistically independent fingerprints of eleven capture subjects. The dynamic database contains uncompressed fingerprint videos of bona fide and attack presentations. Data acquisition, storage, and management were carried out through a systematic study following the general data protection regulation (GDPR) directive. Data were collected from genuine fingerprints and seven PAI species using two commercial fingerprint sensors. Since the sensors do not support a video acquisition mode, a customized acquisition tool is developed using the sensors' SDKs in order to capture the sequence of frames (video) instead of acquiring a single image. The description of the main components of the database is as follows:  
**Participants**  
Eleven capture subjects, four females and seven males, have participated in the data collection. Each subject donated his or her biometric samples from 6 fingers: thumb, index, and middle of both hands. With this in mind, we ended up with a total of 66 statistically independent fingerprints. **Presentation scenario**  
Initially, the participants were given a brief overview of the typical use cases of fingerprint sensors. They then were asked to present their fingerprints to the sensors, knowing that each sensor acquires the complete placement over its surface as a video. The presentations were collected assuming two operational scenario:  
1. Ordinary presentation: which is the typesal placement of the fingertip over the sensor's surface;
2. Pressure presentation: the participants perform additional pressure during the presentation on the sensor's surface. **Sensors** \begin{table}
\begin{tabular}{c c} \hline \hline
**Participants** & 11 capture subjects \\ \hline
**Number of fingerprints** & 66 fingerprints \\
**Acquisition scenario** & 1. Ordinary presentations \\  & 2. Presentations with pressure \\
**Presentation types** & 1. Bona fide \\  & 2. cooperative attacks \\
**Total acquired videos per scenario** & 3564 (792 bona fide and 2772 attacks) \\
**Total acquired videos** & 7128 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: The database. Two sensing technologies with different capabilities are utilized to collect the data. The sensors produce different characteristics for the captured videos due to their distinctions in Table 4.  
**Attacks**  
The attacks are conducted in cooperation with the subjects. The 3D silicon molds were collected from the selected 66 fingerprints. Only one mold was collected from each fingerprint. Accordingly, the attacker performed attack presentations using seven PAI species, specifically: Play-Doh, white glue, spray rubber, nail polish, nail hardener, gelatin, and latex. Table 6 lists the details of the attacks following the recommendations of ISO/IEC 30107-3. **Attacker**  
The attacker has extensive knowledge in biometric recognition, fingerprint sensing technologies, PAs, and PAD methods. Additionally, the attacker has previous practical experiences in attacking fingerprint sensors. During this experiment, the attacker has unlimited access to the fingerprint sensors and has the opportunity to apply attacks without restrictions.