Upload
ava-forbes
View
218
Download
3
Tags:
Embed Size (px)
Citation preview
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 ]
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
Copyright2010
3
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
Copyright2010
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
Copyright2010
5
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
Copyright2010
6
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
Copyright2010
7
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
Copyright2010
8
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
Copyright2010
9
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
Copyright2010
10
Location and Tracking of Vehicles Automated Number Plate Recognition (ANPR)
Appropriate, 'Blacklist in Camera' Architecture
Tightly-
CoupledProcessing
Sources ofData-SetsOperational
PolicingAlertsCamera
& OCRPoliceCarsAlerts
Copyright2010
11
Location and Tracking of Vehicles Automated Number Plate Recognition (ANPR)
Appropriate, 'Blacklist in Camera' Architecture
Tightly-
CoupledProcessing
Sources ofData-SetsOperational
PolicingAlertsCamera
& OCRPoliceCarsAlerts
Blacklists
AlertsOnly
Copyright2010
12
Location and Tracking of Vehicles Automated Number Plate Recognition (ANPR)
ANPR for Mass Surveillance
Camera& OCRHolders ofData-SetsOperational
PolicingPoliceCarsAlertsQuery
and Response
Copyright2010
13
Location and Tracking of Vehicles Automated Number Plate Recognition (ANPR)
ANPR for Mass Surveillance
Camera& OCRHolders ofData-SetsOperational
PolicingPoliceCarsAlertsQuery
and Response
All CapturedVehicle Ids
Copyright2010
14
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
Copyright2010
15
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
??
Copyright2010
16
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.
Copyright2010
17
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.
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