  In recent years, social media has played an increasingly important role in
reporting world events. The publication of crowd-sourced photographs and videos
in near real-time is one of the reasons behind the high impact. However, the
use of a camera can draw the photographer into a situation of conflict.
Examples include the use of cameras by regulators collecting evidence of Mafia
operations; citizens collecting evidence of corruption at a public service
outlet; and political dissidents protesting at public rallies. In all these
cases, the published images contain fairly unambiguous clues about the location
of the photographer (scene viewpoint information). In the presence of adversary
operated cameras, it can be easy to identify the photographer by also combining
leaked information from the photographs themselves. We call this the camera
location detection attack. We propose and review defense techniques against
such attacks. Defenses such as image obfuscation techniques do not protect
camera-location information; current anonymous publication technologies do not
help either. However, the use of view synthesis algorithms could be a promising
step in the direction of providing probabilistic privacy guarantees.
