5G Positioning: Security and Privacy Aspects 283
The simplest example of a mobile‐centric approach is when the user has a GNSS
engine on his/her mobile device and has geo‐maps downloaded into the device memory; thus, the position is calculated entirely based on the memory maps and the GNSS
signals, and such a position estimate can fully preserve the user privacy if not sent
further to the LBSP. An example of a network‐centric position is cell‐ID positioning,
when the network identifies first the serving “cell” or the serving base station of the
user, and then estimates the user location to be within a certain radius (a few tens of
meters to a few tens of kilometers) from the identified cell. In this situation, the user
position is no longer private, as it is already known by LISP.
● The Location Information Collaborator (LIC): can be present or absent and refers to
any other mobile user in the network with whom the desired end‐user can collaborate. Indeed, 5G standard supports Device‐to‐Device (D2D) communications
and collaborative communications, and such collaboration can also serve in positioning phase.
In all the interactions between the localization chain players shown in Figure 13.1,
there are various threats and weak points that can affect the security and privacy of the
users’ position.
13.2 Outdoor versus Indoor Positioning Technologies
While many positioning technologies exist nowadays, there is no winning standalone
technology able to offer good coverage and high accuracy in both indoor and outdoor
scenarios. There are several differences between indoor and outdoor positioning. First,
the outdoor areas, unlike indoor areas, can typically receive satellite signals at a power
sufficiently high to allow communications and positioning, while satellite signals are
highly attenuated by walls and windows, and barely penetrate the indoor spaces. Second,
the outdoor maps are nowadays highly available and highly accurate, while indoor 3D
mapping is still an area with many unsolved challenges, such as proprietary map information, privacy issues, non‐standardized reference systems, etc. The main positioning
technologies available nowadays are summarized in Table 13.1 and their main underlying positioning mechanisms are briefly overviewed in Section 13.3.
13.3 Passive versus Active Positioning
The dichotomy between positioning and communication architectures in 5G is illustrated in Figure 13.2, where the upper plots (a,b,c) explain the positioning‐related concepts, and the lower plots (e,f ) explain the communication‐related concepts. In both
cases, we talk about cell‐ or network‐centric versus device‐centric architectures, but the
terminology is slightly different. In positioning, the unit‐centric terminology refers to
the unit that actually computes the location. The other unit (network or mobile device)
can provide measurements or other signaling sequences to the unit that has the location
engine. In addition, when several mobile devices interchange data useful for position
estimation (e.g. various measurements or other signaling sequences), we talk about
The simplest example of a mobile‐centric approach is when the user has a GNSS
engine on his/her mobile device and has geo‐maps downloaded into the device memory; thus, the position is calculated entirely based on the memory maps and the GNSS
signals, and such a position estimate can fully preserve the user privacy if not sent
further to the LBSP. An example of a network‐centric position is cell‐ID positioning,
when the network identifies first the serving “cell” or the serving base station of the
user, and then estimates the user location to be within a certain radius (a few tens of
meters to a few tens of kilometers) from the identified cell. In this situation, the user
position is no longer private, as it is already known by LISP.
● The Location Information Collaborator (LIC): can be present or absent and refers to
any other mobile user in the network with whom the desired end‐user can collaborate. Indeed, 5G standard supports Device‐to‐Device (D2D) communications
and collaborative communications, and such collaboration can also serve in positioning phase.
In all the interactions between the localization chain players shown in Figure 13.1,
there are various threats and weak points that can affect the security and privacy of the
users’ position.
13.2 Outdoor versus Indoor Positioning Technologies
While many positioning technologies exist nowadays, there is no winning standalone
technology able to offer good coverage and high accuracy in both indoor and outdoor
scenarios. There are several differences between indoor and outdoor positioning. First,
the outdoor areas, unlike indoor areas, can typically receive satellite signals at a power
sufficiently high to allow communications and positioning, while satellite signals are
highly attenuated by walls and windows, and barely penetrate the indoor spaces. Second,
the outdoor maps are nowadays highly available and highly accurate, while indoor 3D
mapping is still an area with many unsolved challenges, such as proprietary map information, privacy issues, non‐standardized reference systems, etc. The main positioning
technologies available nowadays are summarized in Table 13.1 and their main underlying positioning mechanisms are briefly overviewed in Section 13.3.
13.3 Passive versus Active Positioning
The dichotomy between positioning and communication architectures in 5G is illustrated in Figure 13.2, where the upper plots (a,b,c) explain the positioning‐related concepts, and the lower plots (e,f ) explain the communication‐related concepts. In both
cases, we talk about cell‐ or network‐centric versus device‐centric architectures, but the
terminology is slightly different. In positioning, the unit‐centric terminology refers to
the unit that actually computes the location. The other unit (network or mobile device)
can provide measurements or other signaling sequences to the unit that has the location
engine. In addition, when several mobile devices interchange data useful for position
estimation (e.g. various measurements or other signaling sequences), we talk about