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Copyright 2010 1 Roger Clarke, Xamax Consultancy, Canberra Visiting Professor in Computer Science, ANU and in Cyberspace Law & Policy, UNSW http://www.rogerclarke.com/II/HCC-1009 {.html, .ppt} HCC Panel on Privacy YGens, iGens and Privacy Geolocation Privacy [ Government Privacy ]

Copyright 2010 1 Roger Clarke, Xamax Consultancy, Canberra Visiting Professor in Computer Science, ANU and in Cyberspace Law & Policy, UNSW

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Page 1: Copyright 2010 1 Roger Clarke, Xamax Consultancy, Canberra Visiting Professor in Computer Science, ANU and in Cyberspace Law & Policy, UNSW

Copyright2010

1

Roger Clarke, Xamax Consultancy, Canberra Visiting Professor in Computer Science, ANU

and in Cyberspace Law & Policy, UNSW

http://www.rogerclarke.com/II/HCC-1009 {.html, .ppt}

HCC Panel on PrivacyYGens, iGens and Privacy

Geolocation Privacy[ Government Privacy ]

Page 2: Copyright 2010 1 Roger Clarke, Xamax Consultancy, Canberra Visiting Professor in Computer Science, ANU and in Cyberspace Law & Policy, UNSW

Copyright2010

2

GenY & iGens – and PrivacyThe Views of Self-Interested IT-Company

CEOs

• “Privacy's dead. Get over it”

• “If you have something that you don't want anyone to know, maybe you shouldn't be doing it in the first place”

• 'The Facebook generation aren't interested in privacy. They prefer self-exposure'

• “Generation ‘1990’ (Young Generation) rarely caring for risks, hardly interested in privacy” – Klaus Brunnstein, 21 Sep 2010

Page 3: Copyright 2010 1 Roger Clarke, Xamax Consultancy, Canberra Visiting Professor in Computer Science, ANU and in Cyberspace Law & Policy, UNSW

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The ‘Generations’

Indicative Indicative Generation Birth-Years Age in 2010Silent / Seniors 1910-45 65-99Baby Boomers – Early 1945-55 55-65Baby Boomers – Late 1955-65 45-55Generation X 1965-80 30-45Generation Y 1980-95 15-30The iGeneration 1995-

0-15

Page 4: Copyright 2010 1 Roger Clarke, Xamax Consultancy, Canberra Visiting Professor in Computer Science, ANU and in Cyberspace Law & Policy, UNSW

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4

GenY & iGens – and Privacy• Youth have always been Risk-Takers• What's changed is that indiscretions

now have much wider reach in space, and in time

Page 5: Copyright 2010 1 Roger Clarke, Xamax Consultancy, Canberra Visiting Professor in Computer Science, ANU and in Cyberspace Law & Policy, UNSW

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GenY & iGens – and Privacy• Youth have always been Risk-Takers• What's changed is that indiscretions

now have much wider reach in space, and in time

• As people mature:• they gain things to hide• they become more risk-averse

Page 6: Copyright 2010 1 Roger Clarke, Xamax Consultancy, Canberra Visiting Professor in Computer Science, ANU and in Cyberspace Law & Policy, UNSW

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GenY & iGens – and Privacy• Youth have always been Risk-Takers• What's changed is that indiscretions now

have much wider reach in space, and in time• As people mature:

• they gain things to hide• they become more risk-averse

• Y-Gens are taking a pounding• iGens have seen all this, and are

circumspect

Page 7: Copyright 2010 1 Roger Clarke, Xamax Consultancy, Canberra Visiting Professor in Computer Science, ANU and in Cyberspace Law & Policy, UNSW

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GenY & iGens – and Privacy• Youth have always been Risk-Takers• What's changed is that indiscretions now

have much wider reach in space, and in time• As people mature:

• they gain things to hide• they become more risk-averse

• Y-Gens are taking a pounding• iGens have seen all this, and are circumspect• Y & i will be much more privacy-conscious

& privacy-demanding than predecessors

http://www.rogerclarke.com/DV/MillGen.html

Page 8: Copyright 2010 1 Roger Clarke, Xamax Consultancy, Canberra Visiting Professor in Computer Science, ANU and in Cyberspace Law & Policy, UNSW

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Location and Tracking of Handsets• Inherent

There is insufficient capacity to broadcast all traffic in all cellsThe network needs to know the cell each mobile is inMobiles transmit registration messages to base-station(s)They do so when nominally switched off or placed on standby

• What’s being tracked:• The SIM-card, through its identifier (IMSI)• The handset, through its entifier (IMEI)• The human user, because

• the SIM-card and/or handset may be registered to a human (id)entity (possibly required by law!)

• the vast majority of handsets are used, for long periods, with a single SIM-card installed, and by a single person

http://www.rogerclarke.com/DV/YAWYB-CWP.html

Page 9: Copyright 2010 1 Roger Clarke, Xamax Consultancy, Canberra Visiting Professor in Computer Science, ANU and in Cyberspace Law & Policy, UNSW

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The Practicability of HandsetLocation and Tracking

• Location is intrinsic to network operation (±e)• Tracking is feasible,

because the handset sends a stream of messages

• Real-Time Tracking is feasible ifthe data-stream is intense (√) & latency is low (√)

• Retrospective Tracking is feasible iflocations are logged (√) & the log is retained (√?)

• Predictive Tracking is feasible ifthe data-stream is intense (√) & latency is low (√)

http://www.rogerclarke.com/DV/PLT.htmlhttp://www.rogerclarke.com/DV/YAWYB-CWP.html

Page 10: Copyright 2010 1 Roger Clarke, Xamax Consultancy, Canberra Visiting Professor in Computer Science, ANU and in Cyberspace Law & Policy, UNSW

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Location and Tracking of Vehicles Automated Number Plate Recognition (ANPR)

Appropriate, 'Blacklist in Camera' Architecture

Tightly-

CoupledProcessing

Sources ofData-SetsOperational

PolicingAlertsCamera

& OCRPoliceCarsAlerts

Page 11: Copyright 2010 1 Roger Clarke, Xamax Consultancy, Canberra Visiting Professor in Computer Science, ANU and in Cyberspace Law & Policy, UNSW

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Location and Tracking of Vehicles Automated Number Plate Recognition (ANPR)

Appropriate, 'Blacklist in Camera' Architecture

Tightly-

CoupledProcessing

Sources ofData-SetsOperational

PolicingAlertsCamera

& OCRPoliceCarsAlerts

Blacklists

AlertsOnly

Page 12: Copyright 2010 1 Roger Clarke, Xamax Consultancy, Canberra Visiting Professor in Computer Science, ANU and in Cyberspace Law & Policy, UNSW

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Location and Tracking of Vehicles Automated Number Plate Recognition (ANPR)

ANPR for Mass Surveillance

Camera& OCRHolders ofData-SetsOperational

PolicingPoliceCarsAlertsQuery

and Response

Page 13: Copyright 2010 1 Roger Clarke, Xamax Consultancy, Canberra Visiting Professor in Computer Science, ANU and in Cyberspace Law & Policy, UNSW

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Location and Tracking of Vehicles Automated Number Plate Recognition (ANPR)

ANPR for Mass Surveillance

Camera& OCRHolders ofData-SetsOperational

PolicingPoliceCarsAlertsQuery

and Response

All CapturedVehicle Ids

Page 14: Copyright 2010 1 Roger Clarke, Xamax Consultancy, Canberra Visiting Professor in Computer Science, ANU and in Cyberspace Law & Policy, UNSW

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Location and Tracking of Vehicles Automated Number Plate Recognition (ANPR)

ANPR for Mass Surveillance

Camera& OCRHolders ofData-SetsOperational

PolicingPoliceCarsAlertsQuery

and Response

All CapturedVehicle Ids

ACVI

Long-TermShared

Data Warehouse

Page 15: Copyright 2010 1 Roger Clarke, Xamax Consultancy, Canberra Visiting Professor in Computer Science, ANU and in Cyberspace Law & Policy, UNSW

Copyright2010

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Location and Tracking of Vehicles Automated Number Plate Recognition (ANPR)

ANPR for Mass Surveillance

Camera& OCRHolders ofData-SetsOperational

PolicingPoliceCarsAlertsQuery

and Response

All CapturedVehicle Ids

ACVI

Long-TermShared

Data Warehouse

??

Page 16: Copyright 2010 1 Roger Clarke, Xamax Consultancy, Canberra Visiting Professor in Computer Science, ANU and in Cyberspace Law & Policy, UNSW

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Privacy Aspects of ANPR for Mass Surveillance

• Indiscriminate collection(all vehicle ids cf. blacklisted vehicle ids)

• Long-term retention• Data Mining to generate suspicions

Camera& OCRHolders ofData-SetsOperational

PolicingPoliceCarsAll capturedvehicle ids

Long-Term Shared

Data Warehouse

AlertsQueryand

Response

a.c.v.i.

Page 17: Copyright 2010 1 Roger Clarke, Xamax Consultancy, Canberra Visiting Professor in Computer Science, ANU and in Cyberspace Law & Policy, UNSW

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Privacy Aspects of ANPR for Mass Surveillance

• Indiscriminate collection(all vehicle ids cf. blacklisted vehicle ids)

• Long-term retention• Data Mining to generate suspicions

• Proposed / implemented byall Aust Police Forces, aided by Crimtrac

Camera& OCRHolders ofData-SetsOperational

PolicingPoliceCarsAll capturedvehicle ids

Long-Term Shared

Data Warehouse

AlertsQueryand

Response

a.c.v.i.

Page 18: Copyright 2010 1 Roger Clarke, Xamax Consultancy, Canberra Visiting Professor in Computer Science, ANU and in Cyberspace Law & Policy, UNSW

Copyright2010

18

Roger Clarke, Xamax Consultancy, Canberra Visiting Professor in Computer Science, ANU

and in Cyberspace Law & Policy, UNSW

YGens, iGens and PrivacyGeolocation Privacy

[ Government Privacy ]

http://www.rogerclarke.com/II/HCC-1009 {.html, .ppt}

HCC Panel on Privacy