7,108 research outputs found
Ensuring compliance with data privacy and usage policies in online services
Online services collect and process a variety of sensitive personal data that is subject to complex privacy and usage policies. Complying with the policies is critical, often legally binding for service providers, but it is challenging as applications are prone to many disclosure threats. We present two compliance systems, Qapla and Pacer, that ensure efficient policy compliance in the face of direct and side-channel disclosures, respectively. Qapla prevents direct disclosures in database-backed applications (e.g., personnel management systems), which are subject to complex access control, data linking, and aggregation policies. Conventional methods inline policy checks with application code. Qapla instead specifies policies directly on the database and enforces them in a database adapter, thus separating compliance from the application code. Pacer prevents network side-channel leaks in cloud applications. A tenant’s secrets may leak via its network traffic shape, which can be observed at shared network links (e.g., network cards, switches). Pacer implements a cloaked tunnel abstraction, which hides secret-dependent variation in tenant’s traffic shape, but allows variations based on non-secret information, enabling secure and efficient use of network resources in the cloud. Both systems require modest development efforts, and incur moderate performance overheads, thus demonstrating their usability.Onlinedienste sammeln und verarbeiten eine Vielzahl sensibler persönlicher Daten, die komplexen Datenschutzrichtlinien unterliegen. Die Einhaltung dieser Richtlinien ist häufig rechtlich bindend für Dienstanbieter und gleichzeitig eine Herausforderung, da Fehler in Anwendungsprogrammen zu einer unabsichtlichen Offenlegung führen können. Wir präsentieren zwei Compliance-Systeme, Qapla und Pacer, die Richtlinien effizient einhalten und gegen direkte und indirekte Offenlegungen durch Seitenkanäle schützen. Qapla verhindert direkte Offenlegungen in datenbankgestützten Anwendungen. Herkömmliche Methoden binden Richtlinienprüfungen in Anwendungscode ein. Stattdessen gibt Qapla Richtlinien direkt in der Datenbank an und setzt sie in einem Datenbankadapter durch. Die Konformität ist somit vom Anwendungscode getrennt. Pacer verhindert Netzwerkseitenkanaloffenlegungen in Cloud-Anwendungen. Geheimnisse eines Nutzers können über die Form des Netzwerkverkehr offengelegt werden, die bei gemeinsam genutzten Netzwerkelementen (z. B. Netzwerkkarten, Switches) beobachtet werden kann. Pacer implementiert eine Tunnelabstraktion, die Geheimnisse im Netzwerkverkehr des Nutzers verbirgt, jedoch Variationen basier- end auf nicht geheimen Informationen zulässt und eine sichere und effiziente Nutzung der Netzwerkressourcen in der Cloud ermöglicht. Beide Systeme erfordern geringen Entwicklungsaufwand und verursachen einen moderaten Leistungsaufwand, wodurch ihre Nützlichkeit demonstriert wird
Secure data sharing and processing in heterogeneous clouds
The extensive cloud adoption among the European Public Sector Players empowered them to own and operate a range of cloud infrastructures. These deployments vary both in the size and capabilities, as well as in the range of employed technologies and processes. The public sector, however, lacks the necessary technology to enable effective, interoperable and secure integration of a multitude of its computing clouds and services. In this work we focus on the federation of private clouds and the approaches that enable secure data sharing and processing among the collaborating infrastructures and services of public entities. We investigate the aspects of access control, data and security policy languages, as well as cryptographic approaches that enable fine-grained security and data processing in semi-trusted environments. We identify the main challenges and frame the future work that serve as an enabler of interoperability among heterogeneous infrastructures and services. Our goal is to enable both security and legal conformance as well as to facilitate transparency, privacy and effectivity of private cloud federations for the public sector needs. © 2015 The Authors
Development of grid frameworks for clinical trials and epidemiological studies
E-Health initiatives such as electronic clinical trials and epidemiological studies require access to and usage of a range of both clinical and other data sets. Such data sets are typically only available over many heterogeneous domains where a plethora of often legacy based or in-house/bespoke IT solutions exist. Considerable efforts and investments are being made across the UK to upgrade the IT infrastructures across the National Health Service (NHS) such as the National Program for IT in the NHS (NPFIT) [1]. However, it is the case that currently independent and largely non-interoperable IT solutions exist across hospitals, trusts, disease registries and GP practices – this includes security as well as more general compute and data infrastructures. Grid technology allows issues of distribution and heterogeneity to be overcome, however the clinical trials domain places special demands on security and data which hitherto the Grid community have not satisfactorily addressed. These challenges are often common across many studies and trials hence the development of a re-usable framework for creation and subsequent management of such infrastructures is highly desirable. In this paper we present the challenges in developing such a framework and outline initial scenarios and prototypes developed within the MRC funded Virtual Organisations for Trials and Epidemiological Studies (VOTES) project [2]
S-FaaS: Trustworthy and Accountable Function-as-a-Service using Intel SGX
Function-as-a-Service (FaaS) is a recent and already very popular paradigm in
cloud computing. The function provider need only specify the function to be
run, usually in a high-level language like JavaScript, and the service provider
orchestrates all the necessary infrastructure and software stacks. The function
provider is only billed for the actual computational resources used by the
function invocation. Compared to previous cloud paradigms, FaaS requires
significantly more fine-grained resource measurement mechanisms, e.g. to
measure compute time and memory usage of a single function invocation with
sub-second accuracy. Thanks to the short duration and stateless nature of
functions, and the availability of multiple open-source frameworks, FaaS
enables non-traditional service providers e.g. individuals or data centers with
spare capacity. However, this exacerbates the challenge of ensuring that
resource consumption is measured accurately and reported reliably. It also
raises the issues of ensuring computation is done correctly and minimizing the
amount of information leaked to service providers.
To address these challenges, we introduce S-FaaS, the first architecture and
implementation of FaaS to provide strong security and accountability guarantees
backed by Intel SGX. To match the dynamic event-driven nature of FaaS, our
design introduces a new key distribution enclave and a novel transitive
attestation protocol. A core contribution of S-FaaS is our set of resource
measurement mechanisms that securely measure compute time inside an enclave,
and actual memory allocations. We have integrated S-FaaS into the popular
OpenWhisk FaaS framework. We evaluate the security of our architecture, the
accuracy of our resource measurement mechanisms, and the performance of our
implementation, showing that our resource measurement mechanisms add less than
6.3% latency on standardized benchmarks
Contextual and Granular Policy Enforcement in Database-backed Applications
Database-backed applications rely on inlined policy checks to process users'
private and confidential data in a policy-compliant manner as traditional
database access control mechanisms cannot enforce complex policies. However,
application bugs due to missed checks are common in such applications, which
result in data breaches. While separating policy from code is a natural
solution, many data protection policies specify restrictions based on the
context in which data is accessed and how the data is used. Enforcing these
restrictions automatically presents significant challenges, as the information
needed to determine context requires a tight coupling between policy
enforcement and an application's implementation. We present Estrela, a
framework for enforcing contextual and granular data access policies. Working
from the observation that API endpoints can be associated with salient
contextual information in most database-backed applications, Estrela allows
developers to specify API-specific restrictions on data access and use. Estrela
provides a clean separation between policy specification and the application's
implementation, which facilitates easier auditing and maintenance of policies.
Policies in Estrela consist of pre-evaluation and post-evaluation conditions,
which provide the means to modulate database access before a query is issued,
and to impose finer-grained constraints on information release after the
evaluation of query, respectively. We build a prototype of Estrela and apply it
to retrofit several real world applications (from 1000-80k LOC) to enforce
different contextual policies. Our evaluation shows that Estrela can enforce
policies with minimal overheads
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