Context analysis of artificial sweat printed fingerprint forgeries: Assessment of properties for forgery detection

In our paper we investigate the attack based on means of artificial sweat printed fingerprint forgeries at crime scenes by studying the attack chain in general and derive potential context properties from the attack, which help to describe the attack more precisely. Based on the attack chain context properties, potential detection and context anomaly properties are derived and suggested as an enabler for proper detection of such forgeries for forensic experts during forensic investigation and interpretation of traces. It is a first study for the discussion with the community to motivate further work addressing open issues in this domain of crime scene forgery detection. Potential means known from biometric analysis as well as from media forensics are included to enhance forensic trace interpretation. In summary, our first systematic study includes a four-step attack chain, 14 main attack context properties (to describe the attack) and 15 correspondingly derived detection and anomaly properties for the forensic expert usage. A first simulation of the application for two exemplary attacks (A and B) shows, how our defined properties can be used, from two viewpoints: which one of properties has the particular attack and which properties might help to identify the trace as a artificial sweat printed fingerprint forgery during investigation of the trace during forensic interpretation (without prior knowing the existence of the attack).