  The burgeoning technology of Mobile Edge Computing is attracting the
traditional LBS and LS to deploy due to its nature characters such as low
latency and location awareness. Although this transplant will avoid the
location privacy threat from the central cloud provider, there still exists the
privacy concerns in the LS of MEC scenario. Location privacy threat arises
during the procedure of the fingerprint localization, and the previous studies
on location privacy are ineffective because of the different threat model and
information semantic. To address the location privacy in MEC environment, we
designed LoPEC, a novel and effective scheme for protecting location privacy
for the MEC devices. By the proper model of the RAN access points, we proposed
the noise-addition method for the fingerprint data, and successfully induce the
attacker from recognizing the real location. Our evaluation proves that LoPEC
effectively prevents the attacker from obtaining the user's location precisely
in both single-point and trajectory scenarios.
