Page 27 - Trust in ICT 2017

Trust in ICT 1

5.2.1 Trusted Data Usage Mechanism in Smart Cities

In big cities, a very large number of people commute between suburbs and the centre on public transport
(e.g., buses and trains). Commuters on these vehicles are usually in quite close proximity, most carry
handheld de-vices with one or more network interfaces (WiFi, Bluetooth, Global System for Mobile
Communications (GSM)), their patterns of mobility are quite “seasonal” (in the sense that they travel usually
at the same time, repeating the same path day after day), and tend to stay on the vehicle for quite a
prolonged period of time. In addition, devices are often diversely equipped: some have Global Positioning
System (GPS) receivers, others have embedded cameras, sensing abilities (e.g., temperature, light), etc. [9].
As a result, a wide variety of services could be occurred or shared among people, through their devices. For
example:
• Location information sharing: a device with a GPS receiver could be serving location information to
others.
• Exact time information: a GSM device could offer this.
• News headlines, stock market levels: someone able to access the Internet through a GPRS phone
could forward fresh information to others.
• Gaming: devices could participate in a shared game for the duration of their trip.
• Software components: new applications/functionalities could be shared and downloaded from a
peer.
• Information about traffic and delays: commuters traveling in different directions could inform each
other’s.
However, at the same time severe trust issues can be observed as more sensitive data is being exchanged
between entities and clearly it is mandatory to have trustworthy communication among each devices and
services. In general, entities must be capable of building up an opinion about every other device/service they
interact with and eventually more authoritative and reliable communication can be built up with the same
pair of hosts.
Initially, peers that have not been encountered will have a neutral reputation, neither positive nor negative.
This value would be increased after successful interactions, while appropriately decreased following
unsatisfactory service deliveries.
This is very essential to resist against malicious attacks like Sybil attacks, where malicious hosts can simply
generate more identities to avoid being punished for past misbehaviours. This would obviously be high in
sensitive operations, such as monetary transfers, and relaxed for minor tasks, such as location information
gathering.

5.2.1.1 Definition
The success of any data sharing platform in smart cities depends on the compliance on data protection
regulations and, beyond legal obligations, on the establishment of trust relationships with participants
sharing their data. For trusted data exchange, each process from sensing to actionable knowledge requires
trust enabled mechanisms such as data perception trust, trustworthy data fusion/mining and reasoning with
trust related policies.
The solution is just to share data to a trusted source (in specific trust domain and specific content of data) by
leveraging a trusted data usage mechanism in which data usage policies should be personalized set. The data
owners can trace back to check how their data is used.
The trust based data usage mechanism allows benefits such as policy enforcement to share data based on
the properties of data consumers, allowing IoT shared platform to keep track of data usage history, and
more importantly allow data owners to monetize their data sharing by allowing them to dynamically
adjusting their policies on the fly.

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