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

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Presentation on theme: "Copyright 2010 1 Roger Clarke, Xamax Consultancy, Canberra Visiting Professor in Computer Science, ANU and in Cyberspace Law & Policy, UNSW"— Presentation transcript:

1 Copyright Roger Clarke, Xamax Consultancy, Canberra Visiting Professor in Computer Science, ANU and in Cyberspace Law & Policy, UNSW {.html,.ppt} HCC Panel on Privacy YGens, iGens and Privacy Geolocation Privacy [ Government Privacy ]

2 Copyright GenY & iGens – and Privacy The 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

3 Copyright The Generations Indicative Indicative GenerationBirth-YearsAge in 2010 Silent / Seniors Baby Boomers – Early Baby Boomers – Late Generation X Generation Y The iGeneration

4 Copyright 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

5 Copyright 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

6 Copyright 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

7 Copyright 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

8 Copyright Location and Tracking of Handsets Inherent There is insufficient capacity to broadcast all traffic in all cells The network needs to know the cell each mobile is in Mobiles transmit registration messages to base-station(s) They do so when nominally switched off or placed on standby Whats 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

9 Copyright The Practicability of Handset Location 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 if the data-stream is intense () & latency is low () Retrospective Tracking is feasible if locations are logged () & the log is retained (?) Predictive Tracking is feasible if the data-stream is intense () & latency is low ()

10 Copyright Location and Tracking of Vehicles Automated Number Plate Recognition (ANPR) Appropriate, 'Blacklist in Camera' Architecture

11 Copyright Location and Tracking of Vehicles Automated Number Plate Recognition (ANPR) Appropriate, 'Blacklist in Camera' Architecture Blacklists Alerts Only

12 Copyright Location and Tracking of Vehicles Automated Number Plate Recognition (ANPR) ANPR for Mass Surveillance

13 Copyright Location and Tracking of Vehicles Automated Number Plate Recognition (ANPR) ANPR for Mass Surveillance All Captured Vehicle Ids

14 Copyright Location and Tracking of Vehicles Automated Number Plate Recognition (ANPR) ANPR for Mass Surveillance All Captured Vehicle Ids ACVI Long-Term Shared Data Warehouse

15 Copyright Location and Tracking of Vehicles Automated Number Plate Recognition (ANPR) ANPR for Mass Surveillance All Captured Vehicle Ids ACVI Long-Term Shared Data Warehouse ??

16 Copyright Privacy Aspects of ANPR for Mass Surveillance Indiscriminate collection (all vehicle ids cf. blacklisted vehicle ids) Long-term retention Data Mining to generate suspicions

17 Copyright 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 by all Aust Police Forces, aided by Crimtrac

18 Copyright Roger Clarke, Xamax Consultancy, Canberra Visiting Professor in Computer Science, ANU and in Cyberspace Law & Policy, UNSW YGens, iGens and Privacy Geolocation Privacy [ Government Privacy ] {.html,.ppt} HCC Panel on Privacy


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