Predictive digital forensic model to track antisocial behavior based on dermatoglyphics

Abstract

Recent trend of antisocial activity monitoring needs advance method to track and reduce relevant crime. Fingerprint used as biometric print for unique access ID and evidence marking in forensic investigation and in financial transaction authentication. Dermatoglyphics markers characteristics can be used to develop forensic model for antisocial activity tracking. Every human contains fingerprints basically categorized in Whorl, Arch, and Loop, which creates unique biometric pattern. Antisocial behavior appeared mainly by impulsivity which is caused by social isolation, depressed mentality, negative thought process, and lack of emotion. Impulsive behavior can be analyzed by Barratt Impulsiveness Scale, Version 11 (BIS-11) and Impulsive/Premeditated Aggression Scale (IPAS) method. Correlative study of finger ridges and impulsive behavior tests can be used to develop advanced precognition technique which can predict antisocial or criminal intent. Digital forensics algorithm can pre-cure potential antisocial issues from dermatoglyphics (fingerprint) and IPAS, BIS-11 study results. This model can also be used in employment procedure, anti-national threat identification, suicidal attempt precautions, advanced criminal investigation, and during court testimony of identity forensics as psychology index.