3,286 research outputs found
ESPOON: Enforcing Encrypted Security Policies in Outsourced Environments
The enforcement of security policies in outsourced environments is still an
open challenge for policy-based systems. On the one hand, taking the
appropriate security decision requires access to the policies. However, if such
access is allowed in an untrusted environment then confidential information
might be leaked by the policies. Current solutions are based on cryptographic
operations that embed security policies with the security mechanism. Therefore,
the enforcement of such policies is performed by allowing the authorised
parties to access the appropriate keys. We believe that such solutions are far
too rigid because they strictly intertwine authorisation policies with the
enforcing mechanism.
In this paper, we want to address the issue of enforcing security policies in
an untrusted environment while protecting the policy confidentiality. Our
solution ESPOON is aiming at providing a clear separation between security
policies and the enforcement mechanism. However, the enforcement mechanism
should learn as less as possible about both the policies and the requester
attributes.Comment: The final version of this paper has been published at ARES 201
ESPOON: Enforcing Security Policies In Outsourced Environments
Data outsourcing is a growing business model offering services to individuals
and enterprises for processing and storing a huge amount of data. It is not
only economical but also promises higher availability, scalability, and more
effective quality of service than in-house solutions. Despite all its benefits,
data outsourcing raises serious security concerns for preserving data
confidentiality. There are solutions for preserving confidentiality of data
while supporting search on the data stored in outsourced environments. However,
such solutions do not support access policies to regulate access to a
particular subset of the stored data.
For complex user management, large enterprises employ Role-Based Access
Controls (RBAC) models for making access decisions based on the role in which a
user is active in. However, RBAC models cannot be deployed in outsourced
environments as they rely on trusted infrastructure in order to regulate access
to the data. The deployment of RBAC models may reveal private information about
sensitive data they aim to protect. In this paper, we aim at filling this gap
by proposing \textbf{} for enforcing RBAC policies in
outsourced environments. enforces RBAC policies in an
encrypted manner where a curious service provider may learn a very limited
information about RBAC policies. We have implemented
and provided its performance evaluation showing a limited overhead, thus
confirming viability of our approach.Comment: The final version of this paper has been accepted for publication in
Elsevier Computers & Security 2013. arXiv admin note: text overlap with
arXiv:1306.482
Privacy Preserving Enforcement of Sensitive Policies in Outsourced and Distributed Environments
The enforcement of sensitive policies in untrusted environments is still an
open challenge for policy-based systems. On the one hand, taking any
appropriate security decision requires access to these policies. On the other
hand, if such access is allowed in an untrusted environment then confidential
information might be leaked by the policies. The key challenge is how to
enforce sensitive policies and protect content in untrusted environments. In
the context of untrusted environments, we mainly distinguish between outsourced
and distributed environments. The most attractive paradigms concerning
outsourced and distributed environments are cloud computing and opportunistic
networks, respectively.
In this dissertation, we present the design, technical and implementation
details of our proposed policy-based access control mechanisms for untrusted
environments. First of all, we provide full confidentiality of access policies
in outsourced environments, where service providers do not learn private
information about policies. We support expressive policies and take into
account contextual information. The system entities do not share any encryption
keys. For complex user management, we offer the full-fledged Role-Based Access
Control (RBAC) policies.
In opportunistic networks, we protect content by specifying expressive
policies. In our proposed approach, brokers match subscriptions against
policies associated with content without compromising privacy of subscribers.
As a result, unauthorised brokers neither gain access to content nor learn
policies and authorised nodes gain access only if they satisfy policies
specified by publishers. Our proposed system provides scalable key management
in which loosely-coupled publishers and subscribers communicate without any
prior contact. Finally, we have developed a prototype of the system that runs
on real smartphones and analysed its performance.Comment: Ph.D. Dissertation. http://eprints-phd.biblio.unitn.it/1124
Privacy-preserving data outsourcing in the cloud via semantic data splitting
Even though cloud computing provides many intrinsic benefits, privacy
concerns related to the lack of control over the storage and management of the
outsourced data still prevent many customers from migrating to the cloud.
Several privacy-protection mechanisms based on a prior encryption of the data
to be outsourced have been proposed. Data encryption offers robust security,
but at the cost of hampering the efficiency of the service and limiting the
functionalities that can be applied over the (encrypted) data stored on cloud
premises. Because both efficiency and functionality are crucial advantages of
cloud computing, in this paper we aim at retaining them by proposing a
privacy-protection mechanism that relies on splitting (clear) data, and on the
distributed storage offered by the increasingly popular notion of multi-clouds.
We propose a semantically-grounded data splitting mechanism that is able to
automatically detect pieces of data that may cause privacy risks and split them
on local premises, so that each chunk does not incur in those risks; then,
chunks of clear data are independently stored into the separate locations of a
multi-cloud, so that external entities cannot have access to the whole
confidential data. Because partial data are stored in clear on cloud premises,
outsourced functionalities are seamlessly and efficiently supported by just
broadcasting queries to the different cloud locations. To enforce a robust
privacy notion, our proposal relies on a privacy model that offers a priori
privacy guarantees; to ensure its feasibility, we have designed heuristic
algorithms that minimize the number of cloud storage locations we need; to show
its potential and generality, we have applied it to the least structured and
most challenging data type: plain textual documents
Tunable Security for Deployable Data Outsourcing
Security mechanisms like encryption negatively affect other software quality characteristics like efficiency. To cope with such trade-offs, it is preferable to build approaches that allow to tune the trade-offs after the implementation and design phase. This book introduces a methodology that can be used to build such tunable approaches. The book shows how the proposed methodology can be applied in the domains of database outsourcing, identity management, and credential management
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