Privacy for Tigers
summary
Mobile GPS tags (thumb-sized, call home three times a day for five years) and camera-trap/photo aggregation power new poaching risks; analysis finds 5–10% of identifiable photos are geotagged and rhino uploads show >2% recent geotags. A security policy framework for Wildbook classifies data by species/location/time, implements context-aware role-based access control and logging for proactive alerts, Microsoft-funded redevelopment underway, and prototypes and feasibility work (e.g. a leopard-spotter smartphone app) are proposed though not yet widely deployed.
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chapters (29)
- 0:00Intro
- 0:30Outline of talk
- 3:32The market demand
- 4:00Fighting wildlife crime
- 5:39The threat from conservancy data
- 6:55Conservancy data (2)
- 8:43OR models of ranger / poacher
- 9:25The new threat from open data
- 10:54Wildlife aggregation sites
- 13:31Sometimes open data can help..
- 15:46The threat model (2)
- 19:44Aggregation and sensitivity
- 21:26Emergent sensitivity
- 25:08The current system (2)
- 25:52The new system
- 26:45Basic Concept of Operations
- 28:56What can go wrong
- 29:56Context-based access control (2)
- 30:48Intrusion detection
- 33:07Can we do access control better?
- 34:21Wildbook comes quite close ...
- 35:11Second-order issues
- 35:54Lessons learned
- 36:17Broader lessons
- 37:39Second example: bitcoin
- 38:35Hacking bitcoin fungibility
- 38:59The punch line
- 40:20Security and citizenship
- 41:47Sustainability more broadly
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