Anti-forensic resistant likelihood ratio computation: A case study using fingerprint biometrics

One of the major utilities of biometrics in the context of crime scene investigation is to identify people. However, in the most sophisticated cases, criminals may introduce the biometric samples of innocent individuals in order to evade their own identities as well as to incriminate the innocent individuals. To date, even a minute suspect of an anti-forensic threat can potentially jeopardize any forensic investigation to the point that a potentially vital piece of evidence suddenly becomes powerless in the court of law. In order to remedy this situation, we propose an anti-forensic resistant likelihood ratio computation that renders the strength of evidence to a level that is proportional to the trustworthiness of the trace, such that a highly credible evidence will bear its full strength of evidence whilst a highly suspicious trace can have its strength of evidence reduced to naught. Using simulation as well as a spoof fingerprint database, we show that the existing likelihood ratio computation is extremely vulnerable to an anti-forensic threat whereas our proposed computation is robust to it, thereby striking the balance between the utility and threat of a trace.