In this chapter, Duckham and Kulik outline and compare four approaches to location privacy protection: regulation, privacy policies, anonymity, and obfuscation. The growing presence of locationally-aware devices (and applications) have increased both the richness of personal location data being gathered, but also the range of actors with access to it.
While measures can be taken to limit the ease of subsequent use, an individual’s location data gains a significant amount of meaning when it is considered in a wider context. The extent to which anonymised data can be used to infer identity by relating trajectory information with other locations and events raises a pressing concern in location privacy.
I would guess that a significant proportion my own sets of preferences and personalities could be guessed from my life’s trajectory data alone, given sufficient context (which might include the trajectory data of other people, or easily obtained information about places and events). For instance, my own musical taste could probably quite easily be deduced directly from the concerts and festivals I’ve attended over my life, from the concerts and festivals attended by others whose trajectory intersects my own, and indirectly from other inferred personality traits.
As outlined in the reading, the meaning that can be derived from aggregated data may be greatly understated existing privacy policy and regulatory standards. Addressing this issue and limiting growing opportunities for privacy breaches will require case studies that further illustrate the predictive power of location-based data.
-slumley