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Computing and Network Sustainability pp 349–357Cite as

Predictive Digital Forensic Model to Track Antisocial Behavior Based on Dermatoglyphics

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Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 75))

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.

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Acknowledgements

The statistical analysis dermatoglyphics and impulsivity project was developed and observed as a research study of Ph.D. to evaluate productive forensics outcome. Data and analysis were projected from correlation analysis of BIS-11 and IPAS tests, which is already explained in the current paper.

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Authors and Affiliations

  1. Raksha Shakti University, Ahmedabad, India

    M. D. Vasan & B. R. Thakar

Authors
  1. M. D. Vasan
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  2. B. R. Thakar
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Correspondence to M. D. Vasan .

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Editors and Affiliations

  1. Department of Computer Science , National Dong Hwa University, Hualien, Taiwan

    Sheng-Lung Peng

  2. Techno India College of Technology, Kolkata, West Bengal, India

    Nilanjan Dey

  3. Poornima University, Jaipur, Rajasthan, India

    Mahesh Bundele

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Vasan, M.D., Thakar, B.R. (2019). Predictive Digital Forensic Model to Track Antisocial Behavior Based on Dermatoglyphics. In: Peng, SL., Dey, N., Bundele, M. (eds) Computing and Network Sustainability. Lecture Notes in Networks and Systems, vol 75. Springer, Singapore. https://doi.org/10.1007/978-981-13-7150-9_37

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  • DOI: https://doi.org/10.1007/978-981-13-7150-9_37

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-7149-3

  • Online ISBN: 978-981-13-7150-9

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