The Next Step in Biometric Data Fusion Ged Griffin APCOA Melbourne 23 February 2011.

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Presentation transcript:

The Next Step in Biometric Data Fusion Ged Griffin APCOA Melbourne 23 February 2011

Biometrics

Types of Systems  Singular  Multiple singular  Multi-modal

Context  Security  Homeland security/border protection  Policing/investigative activity

Reasons for Use  Identity Verification  Identification of person  Person in custody  Watchlist  Human remains  Crime scene

Typical Operation Input/ Capture Signal Processing Output/ Decision Template Creation/ Storage Template Search/ Comparison

Sensor Iris Retina DNA Fac. Rec. F/Print Extraction Iris Retina DNA Fac. Rec. F/Print Matching Iris Retina DNA Fac. Rec. F/Print Decision Biometric Data Fusion

Biometric Maturity

Considerations  Maturity of biometric products (esp. multimodal)  Next Generation Identification (NGI)  Impact of transnational organised crime  Convergence of biometrics and forensic science  Application of multi-media data fusion techniques on biometrics and forensic science  Improved capabilities through advancements in information and communications technology (Cloud computing & quantum computing)  Proliferation of mobile devices  “Enter once, search many” operation

Policing Investigative Activity  What is an investigation? “an investigation is a search for the truth, in the interests of justice and in accordance with the specifications of the law”  What does an investigator need to establish 1.Has a crime been committed 2.Identity of the offender(s) 3.Location of the offender(s) 4.Connection between the offender and the offence

Crime Scene  Primary  Secondary  Locard’s principle of exchange, ‘every contact leaves its trace’  Evidence located  Searchable  Identifiable  Probative weight  Intelligence value

Biometrics Personal Physical Behavioural Environmental Bioinformatics Commodity Bioinformatics Data Fusion Decision/ Action Linking Biometrics and Forensic Science

Bioinformatics  National DNA databases for plants, animals, birds, and insects  Geo-referenced templates may help to locate unique geographical areas  Help in the management of animal/plant disease and bio- containment strategies  Identify stolen animals and stock  Identify owners in animal welfare investigation  Identify owners of animals in criminal investigations and local enforcement (animal hair at crime scenes, dog attacks and fecial deposits in public spaces)

Commodity - Drugs  Organic drugs - DNA analysis  Synthetic drugs chemical composition  Pattern recognition of images on packaging  Automated extraction and matching of pill press impressions/features

Commodity – Tool Marks  Tool mark examination and firearm/ballistic examination  Develop templates for common articles (eg. shoe impressions)  Reactive or Proactive  Capture and storage of images of known and recovered firearms

The future  Forensic multi-media data fusion and information retrieval platform  Consideration of evidence in the context of all other evidence  Open architecture to support interoperability  Integrated/networked computerised system(s)  Facilitate high volumes of transactions and fast turn around  Processing scalability and matcher performance scalability

Ged Griffin Mb: