09/13 Notes Chapter 1
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Recognition
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Either:
 * verification
 * identification

Verification
 * 1 to 1 matching
 * identity is clamed
    * i.e. Iphone verifying owner fingerprint (1 identity)
 * output is yes or no (genunine or imposter)
 
Identification
 * 1 to N matching
 * Asks system "Who am I?"
    * No identity is clamed
 * Output is Identity or no match (not binary since multiple ids)

De-Duplication
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Avoid duplication of identities
 * similar to identification

Traits
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Trait should *ideally* be
 #. Unique or distinctive
 #. Easy to collect
 #. Permanence (does it completely change?)
 #. Universality (most humans have this trait)
 #. Integrity (is it easy to replicate?)
     * Trait is resiliant to circumvention
        * Spoofing and obfuscating
 #. Performance (how easy is it to get information from the trait?)
 #. Acceptability (how willing is population to give trait?)
 

System / Applications
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 #. Cooperative vs Non-cooperative user(bank user vs criminal at station)
 #. Overt vs Covert Deployment
 #. Habituated vs Non-Habituated users (used to getting data collected or not)
 #. Attended vs Unattended operation (does the user require human interaction)
 #. Control vs Uncontrolled (environment is very controlled vs not)
 #. Closed vs Open (data is not shared with another application or is shared)