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Copyright 2008-09 1 Roger Clarke Xamax Consultancy, Canberra Visiting Professor at ANU, UNSW, and the Uni. of Hong Kong Chair, Australian Privacy Foundation.

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Presentation on theme: "Copyright 2008-09 1 Roger Clarke Xamax Consultancy, Canberra Visiting Professor at ANU, UNSW, and the Uni. of Hong Kong Chair, Australian Privacy Foundation."— Presentation transcript:

1 Copyright 2008-09 1 Roger Clarke Xamax Consultancy, Canberra Visiting Professor at ANU, UNSW, and the Uni. of Hong Kong Chair, Australian Privacy Foundation {.html,.ppt} Social Implications of Covert Policing Workshop – 7 April 2009 The Covert Implementation of Mass Vehicle Surveillance in Australia

2 Copyright 2008-09 2 Red Light and Speed Cameras

3 Copyright 2008-09 3 Cynicism about Red Light and Speed Cameras (Vic)

4 Copyright 2008-09 4 Covert Implementation of Mass Vehicle Surveillance AGENDA Red-Light / Speed Cameras to ANPR Traffic Applications Blacklist-in-Camera Architecture Quality Factors LEAs – Operational Applications LEAs – Intelligence Applications Mass Surveillance ANPR ANPR Deployments in Australia ANPR Coordination in Australia

5 Copyright 2008-09 5 Beyond Red Light / Speed Cameras To Vehicle Surveillance Vehicles can be monitored in various ways, e.g. Manual Inspection of VINs, registration plates Passive RFID-tags passing control-points On-Board Transmitters, with self-reporting of GPS-based or other coordinates Vehicle Registration Data can be monitored: Cameras were wet chemistry, are now digital Data Extraction was manual, is now automated Auto-Lookup of Blacklists is now feasible

6 Copyright 2008-09 6 Automated Number Plate Recognition (ANPR)

7 Copyright 2008-09 7 Automated Number Plate Recognition (ANPR) A Digital Camera Captures an image of a motor vehicles 'number' plate Software Extracts the registration data (numbers, letters, perhaps other data such as colour and jurisdiction identifiers) List(s) of Numbers Being Sought Enables evaluation of the significance of the extracted data Transmission Facilities Sends the extracted data and perhaps other data elsewhere

8 Copyright 2008-09 8 Traffic Applications Traffic Law Enforcement. Detection and prosecution for: running red lights driving at a point-in-time speed over the speed limit Traffic Law Enforcement. Detection and interception of: Unregistered Vehicles ?Driving at an average speed over the speed limit ??Vehicles owned by currently Unlicensed Drivers Public Safety. Deterrence of unsafe practices, e.g. running red lights, speeding ?driving unregistered vehicles ??driving while unlicensed

9 Copyright 2008-09 9 'Blacklist in Camera' ANPR Architecture

10 Copyright 2008-09 10 'Blacklist in Camera' ANPR Architecture

11 Copyright 2008-09 11 'Blacklist in Camera' ANPR Architecture

12 Copyright 2008-09 12 ANPR Quality Alliances of purveyors and purchasers suggest that data extraction is accurate and reliable... BUT... Very little evidence is publicly available There appear to be no independent tests Many factors reduce reliability, including: the nature and condition of the registration plates the condition of the camera lens the conditions of the light-path and back-lighting The extraction is by its nature 'fuzzy', and confidence threshholds have to be set Reliable extraction of the registration data may be as low as 70% even under favourable conditions

13 Copyright 2008-09 13 ANPR Traffic Applications Some Implications Deterrence of Targeted Behaviour Targeted Fines and Points Deductions Substantial Resources Required, in particular Police Cars Downstream False-Negatives Escape False-Positives Suffer: Financial Impacts Licence-Retention Impacts

14 Copyright 2008-09 14 LEAs – Operational Applications Detection and Interception of: Wanted Vehicles, in particular: 'Reported Stolen' 'Get-Away Cars' Vehicles associated with Persons of Interest Dependent on: Real-Time Acccess to... Real-Time-Maintained Data Sources

15 Copyright 2008-09 15 LEA Operational Applications Quality Factors and Implications Data-Source Quality Factors are critical, esp. Accuracy, Precision and Currency (Rare?) Instances of Large Benefits (Common?) Instances of Error: High Risk to Vehicle Occupants because of the Interceptor's Suspicions Substantial Embarrassment, Confusion Likelihood of Collateral Police Actions – arbitrary vehicle inspection, search

16 Copyright 2008-09 16 LEAs – Intelligence Applications Retrospective Analysis of Vehicle Movements: Detection of Duplicates False Registration Numbers Retrospective Inferences about Owner Location and Movements Retrospective Inferences about Co-Location, and Co-Location Frequency, of: Vehicles People Real-Time Inferences about Location, Co-Location

17 Copyright 2008-09 17 Mass Surveillance ANPR Architecture

18 Copyright 2008-09 18 Mass Surveillance ANPR Architecture

19 Copyright 2008-09 19 LEAs – Intelligence Applications Quality Factors Unreliable Extraction of Registration Data Data Collection Speculative i.e. without Due Cause / Reasonable Grounds for Suspicion This protection is a foundation of a free society Retention Periods unclear and possibly very long Use of Probabilistic (Speculative) Data Mining in order to generate suspicions

20 Copyright 2008-09 20 ANPR Deployments in Australia In most States and Territories, one or more agencies has deployed or at least piloted ANPR 300-400 cameras acquired, some currently operational One longstanding application exists: NSW RTA Safe-T-Cam for trucks 24 fixed-location cameras since 1989 relatively recently migrated to ANPR

21 Copyright 2008-09 21 Features of ANPR Deployments in Australia Every Single Deployment Lacks: Explicit Legal Authority Public Justification Public Information Public Consultation Operational Transparency Effective Regulatory Control Effective Privacy Laws

22 Copyright 2008-09 22 Submissions expressing serious concern about privacy: APF OFPC OVPC QCCL

23 Copyright 2008-09 23 OVPC: "The whole concept of an individuals right to anonymity is sacrificed: it is no longer possible to drive on a public road anonymously, even if one is doing nothing wrong" OFPC: "ANPR can result in the routine collection of the personal information of large numbers of people. For many of these people, there may be no cause for suspicion and hence no reason to collect information about them. A widespread ANPR system may permit government agencies to track a large number of vehicles (and individuals), revealing where individuals have been, when and potentially with whom. Other than in specific circumstances, this does not seem to be information that government agencies would routinely need to know about members of the community... The Office would caution against establishing infrastructure that could [be] used in such an expansive and invasive manner"

24 Copyright 2008-09 24 Recommendations of the Qld Parliamentary Committee: [because there is no current justification,] further research of the road safety benefits of ANPR [because the proposal is so privacy-intrusive,] crucial legislative safeguards... to protect... privacy [because quality is low,] the resolution of technical problems that prevent ANPR devices reading some number plate designs

25 Copyright 2008-09 25 Coordinative Activities by Crimtrac The national LEA information systems operator (e.g. fingerprint, DNA databases) Given $2.3m for an 'ANPR Scoping Study' 2007-08 Privacy Issues Analysis conducted Nov 2007 "We have not yet determined exactly the extent to which we would capture all data. It may well be that we only capture hot list data" (Transcript of Evidence to Qld Parltry Travelsafe Committee, 14 Mar 2008, p. 17) PIA and Consultation (Jun-Nov 2008)

26 Copyright 2008-09 26 Crimtrac's PIA Consultation Paper June 2008 "... the system will collect and store... all sightings of all vehicle passengers" A 'National Automated Vehicle Recognition System' (NAVR) "data-matching to identify alerts would take place centrally..." "sightings would be collected for all vehicles passing a camera site, and would contain an overhead image of the vehicle at sufficient resolution so that the driver or passenger could be identified if appropriate "[from] 300 fixed and 100 mobile to 4000 fixed and 500 mobile cameras" "all ANPR data would be held for five years" an indicative 70 million sightings per day – implying 127 billion photographs and associated metadata over a rolling 5-year cycle

27 Copyright 2008-09 27 Crimtrac's Untrustworthiness The position established in May 2008 is inconsistent with the statements of mid-Mar 2008 Committed to Mass Surveillance ANPR Expressly Facilitative of Mass Surveillance No Consideration of the negative consequences PIA Report withheld, despite an understanding it would be published Scoping Study Report withheld

28 Copyright 2008-09 28 Covert Implementation of Mass Vehicle Surveillance Conclusions LEAs are implementing ANPR covertly i.e. without full public information, without oversight, without express authority LEAs are using Mass Surveillance ANPR, not Blackist-in-Camera architecture Crimtrac is implementing the facilitative mechanism for Mass Surveillance ANPR After initially adopting some degree of openness, Crimtrac is operating covertly

29 Copyright 2008-09 29 Covert Implementation of Mass Vehicle Surveillance Implications For LEAs A further step in the slide into untrustworthiness Greatly increased risk of behaviour above the law Greatly increased risk of serious public distrust For Australian society A profound reduction in civil liberties A groundbreaker for a surveillance society A major contributor to social breakdown and anarchic behaviour

30 Copyright 2008-09 30 Covert Implementation of Mass Vehicle Surveillance Policy Implications ANPR is a litmus test of the Rudd Government's capacity to withstand the backroom pressure put on it by the law enforcement community The Australian public wants law enforcement agencies to have appropriate technology and appropriate powers... but not to the extent that freedoms and democracy are undermined

31 Copyright 2008-09 31 Counterveillance Principles 1.Independent Evaluation of Technology 2.A Moratorium on Technology Deployments 3.Open Information Flows 4.Justification for Proposed Measures 5.Consultation and Participation 6.Evaluation 7.Design Principles 1.Balance 2.Independent Controls 3.Nymity and Multiple Identity 8.Rollback

32 Copyright 2008-09 32 Roger Clarke Xamax Consultancy, Canberra Visiting Professor at ANU, UNSW, and the Uni. of Hong Kong Chair, Australian Privacy Foundation {.html,.ppt} Social Implications of Covert Policing Workshop – 7 April 2009 The Covert Implementation of Mass Vehicle Surveillance in Australia

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