15,398 research outputs found
DTKI: a new formalized PKI with no trusted parties
The security of public key validation protocols for web-based applications
has recently attracted attention because of weaknesses in the certificate
authority model, and consequent attacks.
Recent proposals using public logs have succeeded in making certificate
management more transparent and verifiable. However, those proposals involve a
fixed set of authorities. This means an oligopoly is created. Another problem
with current log-based system is their heavy reliance on trusted parties that
monitor the logs.
We propose a distributed transparent key infrastructure (DTKI), which greatly
reduces the oligopoly of service providers and allows verification of the
behaviour of trusted parties. In addition, this paper formalises the public log
data structure and provides a formal analysis of the security that DTKI
guarantees.Comment: 19 page
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Web Service Trust: Towards A Dynamic Assessment Framework
Trust in software services is a key prerequisite for the success and wide adoption of services-oriented computing (SOC) in an open Internet world. However, trust is poorly assessed by existing methods and technologies, especially in dynamically composed and deployed SOC systems. In this paper, we discuss current methods for assessing trust in service-oriented computing and identify gaps of current platforms, in particular with regards to runtime trust assessment. To address these gaps, we propose a model of runtime trust assessment of software services and introduce a framework for realizing the model. A key characteristic of our approach is the support that it offers for customizable assessment of trust based on evidence collected during the operation of software services and its ability to combine this evidence with subjective assessments coming from service clients
Medians and Beyond: New Aggregation Techniques for Sensor Networks
Wireless sensor networks offer the potential to span and monitor large
geographical areas inexpensively. Sensors, however, have significant power
constraint (battery life), making communication very expensive. Another
important issue in the context of sensor-based information systems is that
individual sensor readings are inherently unreliable. In order to address these
two aspects, sensor database systems like TinyDB and Cougar enable in-network
data aggregation to reduce the communication cost and improve reliability. The
existing data aggregation techniques, however, are limited to relatively simple
types of queries such as SUM, COUNT, AVG, and MIN/MAX. In this paper we propose
a data aggregation scheme that significantly extends the class of queries that
can be answered using sensor networks. These queries include (approximate)
quantiles, such as the median, the most frequent data values, such as the
consensus value, a histogram of the data distribution, as well as range
queries. In our scheme, each sensor aggregates the data it has received from
other sensors into a fixed (user specified) size message. We provide strict
theoretical guarantees on the approximation quality of the queries in terms of
the message size. We evaluate the performance of our aggregation scheme by
simulation and demonstrate its accuracy, scalability and low resource
utilization for highly variable input data sets
Data Leak Detection As a Service: Challenges and Solutions
We describe a network-based data-leak detection (DLD)
technique, the main feature of which is that the detection
does not require the data owner to reveal the content of the
sensitive data. Instead, only a small amount of specialized
digests are needed. Our technique – referred to as the fuzzy
fingerprint – can be used to detect accidental data leaks due
to human errors or application flaws. The privacy-preserving
feature of our algorithms minimizes the exposure of sensitive
data and enables the data owner to safely delegate the
detection to others.We describe how cloud providers can offer
their customers data-leak detection as an add-on service
with strong privacy guarantees.
We perform extensive experimental evaluation on the privacy,
efficiency, accuracy and noise tolerance of our techniques.
Our evaluation results under various data-leak scenarios
and setups show that our method can support accurate
detection with very small number of false alarms, even
when the presentation of the data has been transformed. It
also indicates that the detection accuracy does not degrade
when partial digests are used. We further provide a quantifiable
method to measure the privacy guarantee offered by our
fuzzy fingerprint framework
Citizen Electronic Identities using TPM 2.0
Electronic Identification (eID) is becoming commonplace in several European
countries. eID is typically used to authenticate to government e-services, but
is also used for other services, such as public transit, e-banking, and
physical security access control. Typical eID tokens take the form of physical
smart cards, but successes in merging eID into phone operator SIM cards show
that eID tokens integrated into a personal device can offer better usability
compared to standalone tokens. At the same time, trusted hardware that enables
secure storage and isolated processing of sensitive data have become
commonplace both on PC platforms as well as mobile devices.
Some time ago, the Trusted Computing Group (TCG) released the version 2.0 of
the Trusted Platform Module (TPM) specification. We propose an eID architecture
based on the new, rich authorization model introduced in the TCGs TPM 2.0. The
goal of the design is to improve the overall security and usability compared to
traditional smart card-based solutions. We also provide, to the best our
knowledge, the first accessible description of the TPM 2.0 authorization model.Comment: This work is based on an earlier work: Citizen Electronic Identities
using TPM 2.0, to appear in the Proceedings of the 4th international workshop
on Trustworthy embedded devices, TrustED'14, November 3, 2014, Scottsdale,
Arizona, USA, http://dx.doi.org/10.1145/2666141.266614
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