  Radio Frequency Identification (RFID) is a technology aimed at eficiently
identifying and tracking goods and assets. Such identification may be performed
without requiring line-of-sight alignment or physical contact between the RFID
tag and the RFID reader, whilst tracking is naturally achieved due to the short
interrogation field of RFID readers. That is why the reduction in price of the
RFID tags has been accompanied with an increasing attention paid to this
technology. However, since tags are resource-constrained devices sending
identification data wirelessly, designing secure and private RFID
identification protocols is a challenging task. This scenario is even more
complex when scalability must be met by those protocols.
  Assuming the existence of a lightweight, secure, private and scalable RFID
identification protocol, there exist other concerns surrounding the RFID
technology. Some of them arise from the technology itself, such as distance
checking, but others are related to the potential of RFID systems to gather
huge amount of tracking data. Publishing and mining such moving objects data is
essential to improve efficiency of supervisory control, assets management and
localisation, transportation, etc. However, obvious privacy threats arise if an
individual can be linked with some of those published trajectories. The present
dissertation contributes to the design of algorithms and protocols aimed at
dealing with the issues explained above. First, we propose a set of protocols
and heuristics based on a distributed architecture that improve the efficiency
of the identification process without compromising privacy or security.
Moreover, we present a novel distance-bounding protocol based on graphs that is
extremely low-resource consuming. Finally, we present two trajectory
anonymisation methods aimed at preserving the individuals' privacy when their
trajectories are released.
