Privacy in Ubiquitous Computing Options, Trends, and Implications of - PowerPoint PPT Presentation

Privacy in Ubiquitous Computing Options, Trends, and Implications of Smart Objects Marc Langheinrich Institut für Pervasive Computing ETH Zürich Februar 11. 2006 ZiF-Workshop: Privacy and 1 Surveillance Technologies

Privacy in Ubiquitous Computing Options, Trends, and Implications of Smart Objects Marc Langheinrich Institut für Pervasive Computing ETH Zürich “By 2010,... privacy will become a meaningless concept in “By 2010,... privacy will become a meaningless concept in Western societies (0.6 probability). Privacy will be forever Western societies (0.6 probability). Privacy will be forever lost because technology will allow us to make sense of the lost because technology will allow us to make sense of the data we collect.” Gartner Research, 2000 data we collect.” Gartner Research, 2000 Februar 11. 2006 ZiF-Workshop: Privacy and 2 Surveillance Technologies

Privacy and Technology � „The right to be let alone.“ � Louis Brandeis, 1890 (Harvard Law Review) � “Numerous mechanical devices threaten to make good the prediction that ‘what is whispered in the closet shall be proclaimed from the housetops’” Louis D. Brandeis, 1856 - 1941 Februar 11. 2006 ZiF-Workshop: Privacy and Surveillance Technologies 3

The Vision of Ubiquitous Computing „The most profound technologies are those that disappear . They weave themselves into the fabric of everyday life until they are indistinguishable from it.“ Mark Weiser (1952 – 1999), XEROX PARC � Basic Motivation of Ubiquitous Computing � The computer as a tool for the everyday � Things are aware of each other and the environment � Integrating computers with intuitive user interfaces Februar 11. 2006 ZiF-Workshop: Privacy and Surveillance Technologies 4

Smart Toaster � Gets weather forecast from the Internet � Can remind you of important dates (from your electronic agenda) Qu Quelle: : http://news.bbc.co.uk/hi/english/sci/tech/newsid_1264000/1254205.stm Februar 11. 2006 ZiF-Workshop: Privacy and Surveillance Technologies 5

Smart Lawn Sprinkler � Lawn Sensor Reports Dryness � Uses Weather Forecast from Internet Februar 11. 2006 ZiF-Workshop: Privacy and Surveillance Technologies 6

Smart Mirror I would suggest � Tips for Wardrobe the Jeans Lieber die blaue Hose with the mit den dunklen Schuhen black shoes Selection, Make-Up today… � Mirror detects color combinations � Closet and Washer know which clothes are available � Takes Mood Into Account � Sensors in underwear � Camera with face recognition Februar 11. 2006 ZiF-Workshop: Privacy and Surveillance Technologies 7

Smart Mirror I would suggest � Tips for Wardrobe the Jeans Lieber die blaue Hose with the mit den dunklen Schuhen black shoes Selection, Make-Up today… � Mirror detects color combinations � Closet and Washer know which clothes are available � Takes Mood Into Account � Sensors in underwear Smart Mirror Prototype at ETH � Camera with face Smart Mirror Prototype at ETH Detects Clothing, Suggests Alternatives recognition Detects Clothing, Suggests Alternatives Based on Generic Color Theory Module Based on Generic Color Theory Module Februar 11. 2006 ZiF-Workshop: Privacy and Surveillance Technologies 8

Instead of „World inside the Computer“... Not Not like this! World inside Computer would be Virtual Reality Februar 11. 2006 ZiF-Workshop: Privacy and Surveillance Technologies 9

„Computer in the World“ ! Ubiquitous Computing Februar 11. 2006 ZiF-Workshop: Privacy and Surveillance Technologies 10

Ubiquitous Computing – Technology Drivers � Miniaturization � Integration into everyday things � New Materials � Novel input/output capabilities � Wireless Communication � Simplifies communication � Facilitates cooperation and coordination � Sensors � „Smartness“ through context-awareness Februar 11. 2006 ZiF-Workshop: Privacy and Surveillance Technologies 11

Ubiquitous Computing – Privacy Implications � Data Collection � Scale (everywhere, anytime) � Kind (unnoticed, invisible) � Reason („stockpiling“ knowledge) � Data Types � Sensory instead of factual � Data Access � „Internet of Things“ Februar 11. 2006 ZiF-Workshop: Privacy and Surveillance Technologies 12

Ubiquitous Computing – Societal Drivers � Higher Efficiency � Lean production (Overproduction, Out-of-Stock) � Targeted Sales (1-1 Marketing) � More Convenience � Finding your way (e.g., travel assistants) � Lower TCO (“total cost of ownership”) w/ pay-per-use � Increased Safety � Homeland security (terrorism, drug trafficking, etc.) � Petty crimes & negligence (e.g., traffic accidents, theft) Februar 11. 2006 ZiF-Workshop: Privacy and Surveillance Technologies 13

Example: Health Industry as Driving Factor for Ubiquitous Computing � Higher Efficiency � Localization system for medical personnel facilitates highly dynamic scheduling � More Convenience � Senior citizens can live independently with the help of a Smart Environment � Increased Safety � Electronically tagged blood packs and smart emergency room lower chances of mistakes Februar 11. 2006 ZiF-Workshop: Privacy and Surveillance Technologies 14

Example: RFID and Retail � CASPIAN vs. Benetton � Benetton announces RFID in Sisley clothing (March 2003) � CASPIAN calls for boycott (www.spychips.com) � Benetton retracts statement (April 2003) � Wal-Mart / Procter & Gamble (Fall 2003) � (Secret) field trial in Broken Arrow, Oklahoma � Track consumer behavior with secret camera & RFID Februar 11. 2006 ZiF-Workshop: Privacy and Surveillance Technologies 15

Example: RFID and Retail � CASPIAN vs. Benetton � Benetton announces RFID in Sisley clothing (March 2003) � CASPIAN calls for boycott (www.spychips.com) � Benetton retracts statement (April 2003) November 2003 � Wal-Mart / Procter & Gamble (Fall 2003) RFID 570,000 RFID and privacy 239,000 (42%) � (Secret) field trial in Broken Arrow, Oklahoma � Track consumer behavior with secret camera & RFID � Public Concern (as measured by Google) � Original numbers by Ravi Pappu, RFID Privacy Workshop @ MIT: November 15, 2003 Februar 11. 2006 ZiF-Workshop: Privacy and Surveillance Technologies 16

Example: RFID and Retail � CASPIAN vs. Benetton � Benetton announces RFID in Sisley clothing (March 2003) � CASPIAN calls for boycott (www.spychips.com) � Benetton retracts statement (April 2003) November 2003 July 2004 � Wal-Mart / Procter & Gamble (Fall 2003) RFID RFID 570,000 2,340,000 RFID and privacy RFID and privacy 1,060,000 (45%) 239,000 (42%) � (Secret) field trial in Broken Arrow, Oklahoma � Track consumer behavior with secret camera & RFID � Public Concern (as measured by Google) � Original numbers by Ravi Pappu, RFID Privacy Workshop @ MIT: November 15, 2003 Februar 11. 2006 ZiF-Workshop: Privacy and Surveillance Technologies 17

Example: RFID and Retail � CASPIAN vs. Benetton � Benetton announces RFID in Sisley clothing (March 2003) � CASPIAN calls for boycott (www.spychips.com) � Benetton retracts statement (April 2003) November 2003 November 2005 July 2004 � Wal-Mart / Procter & Gamble (Fall 2003) RFID RFID RFID 4,550,000 2,340,000 570,000 RFID and privacy RFID and privacy RFID and privacy 239,000 (42%) 1,060,000 (45%) 3,110,000 (68%) � (Secret) field trial in Broken Arrow, Oklahoma � Track consumer behavior with secret camera & RFID � Public Concern (as measured by Google) � Original numbers by Ravi Pappu, RFID Privacy Workshop @ MIT: November 15, 2003 Februar 11. 2006 ZiF-Workshop: Privacy and Surveillance Technologies 18

Example: RFID and Retail � CASPIAN vs. Benetton � Benetton announces RFID in Sisley clothing (March 2003) � CASPIAN calls for boycott (www.spychips.com) � Benetton retracts statement (April 2003) November 2003 November 2005 July 2004 � Wal-Mart / Procter & Gamble (Fall 2003) RFID RFID RFID 4,550,000 2,340,000 570,000 RFID and privacy RFID and privacy RFID and privacy 239,000 (42%) 1,060,000 (45%) 3,110,000 (68%) � (Secret) field trial in Broken Arrow, Oklahoma � Track consumer behavior with secret camera & RFID � Public Concern (as measured by Google) � Original numbers by Ravi Pappu, RFID Privacy Workshop @ MIT: November 15, 2003 Februar 11. 2006 ZiF-Workshop: Privacy and Surveillance Technologies 19

Example: RFID and Retail � Emnid Survey Germany (03/2002) � 50% have at least one loyalty card � 72% welcome such offers � 70 Million Cards in Circulation (12/2003) � Average rebate: 1.0-0.5% � 15% of consumers estimate rebate being 5-10% � Minding the Fine Print? � Explicit signature allows detailed data mining � Consequences? Februar 11. 2006 ZiF-Workshop: Privacy and Surveillance Technologies 20

Consumer Loyalty Cards – The Dark Side � The Story of Robert Riveras (1998) � Slipped on spilled yoghurt and hurt kneecap. Sued. � Consumer card showed high volume licqour purchases � Settled out of court � Or: Divorce Case � Liking of expensive wines increased alimony payments Februar 11. 2006 ZiF-Workshop: Privacy and Surveillance Technologies 21