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by the hospital to face emergency situations. Pre-
venting such actions may be critical for the life of
the patient. To address this problem, we need to de-
fine acceptable infringements and metrics for assess-
ing privacy risks by performing real-time risk analy-
sis. This make it possible to narrow down the number
of situations where rightful data usage is under inves-
tigation by considering only situations whose privacy
risks cannot be tolerated by the data subject.
Outsourcing is becoming a common business
practice of many organizations. This business strat-
egy is adopted to reduce costs, but it involves trans-
fer of business activities and data to an external sup-
plier. Suppose that the hospital outsources some ther-
apeutic activities to a subcontractor together with the
data needed for its execution. The hospital is no
more in control of such data. Therefore, it needs ev-
idence that the subcontractor has used the informa-
tion only for providing therapeutic treatments. To
address those requirements for data protection policy
compliance in distributed systems, we need an infras-
tructure that supports different security mechanisms
as well as infringement management. The infrastruc-
ture should allow seamless interoperability of differ-
ent enforcement mechanism, such as DRM, and on
the other hand deterring security mechanism such as
audit logic. This also requires real-time risk analy-
sis models that make it possible to define at run-time
flexible boundaries between preventive and deterring
mechanisms (i.e., dynamically select the most proper
mechanism for a certain situation based on the risks it
involves).
4 CONCLUSIONS
This paper has defined the basis for the development
of more trustworthy and privacy-awareIT systems. In
particular, this work intends
• support organizations in ensuring compliance
with data protection policies as the ability of iden-
tifying policy infringements will provide a con-
crete way to ensure organizations that they are
meeting their privacy promises;
• make users more accountable for their actions as
user behavior will be analyzed and possible mis-
conducts detected;
• be more flexible to deal with exceptions as the a-
posteriori policy compliance would make it pos-
sible to continue operations and account users for
eventual misconduct afterwards;
• provide more usable and scalable tools which will
automate many operations that are currently per-
formed by humans.
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