14,112 research outputs found
eIDeCert: a user-centric solution for mobile identification
The necessity to certify one's identity for different purposes and the evolution of mobile technologies have led to the generation of electronic devices such as smart cards, and electronic identities designed to meet daily needs. Nevertheless, these mechanisms have a problem: they don't allow the user to set the scope of the information presented. That problem introduces interesting security and privacy challenges and requires the development of a new tool that supports user-centrity for the information being handled. This article presents eIDeCert, a tool for the management of electronic identities (eIDs) in a mobile environment with a user-centric approach. Taking advantage of existing eCert technology we will be able to solve a real problem. On the other hand, the application takes us to the boundary of what the technology can cope with: we will assess how close we are to the boundary, and we will present an idea of what the next step should be to enable us to reach the goal
SGXIO: Generic Trusted I/O Path for Intel SGX
Application security traditionally strongly relies upon security of the
underlying operating system. However, operating systems often fall victim to
software attacks, compromising security of applications as well. To overcome
this dependency, Intel introduced SGX, which allows to protect application code
against a subverted or malicious OS by running it in a hardware-protected
enclave. However, SGX lacks support for generic trusted I/O paths to protect
user input and output between enclaves and I/O devices.
This work presents SGXIO, a generic trusted path architecture for SGX,
allowing user applications to run securely on top of an untrusted OS, while at
the same time supporting trusted paths to generic I/O devices. To achieve this,
SGXIO combines the benefits of SGX's easy programming model with traditional
hypervisor-based trusted path architectures. Moreover, SGXIO can tweak insecure
debug enclaves to behave like secure production enclaves. SGXIO surpasses
traditional use cases in cloud computing and makes SGX technology usable for
protecting user-centric, local applications against kernel-level keyloggers and
likewise. It is compatible to unmodified operating systems and works on a
modern commodity notebook out of the box. Hence, SGXIO is particularly
promising for the broad x86 community to which SGX is readily available.Comment: To appear in CODASPY'1
Content-Aware DataGuides for Indexing Large Collections of XML Documents
XML is well-suited for modelling structured data with
textual content. However, most indexing approaches perform
structure and content matching independently, combining
the retrieved path and keyword occurrences in a third
step. This paper shows that retrieval in XML documents can
be accelerated significantly by processing text and structure
simultaneously during all retrieval phases. To this end,
the Content-Aware DataGuide (CADG) enhances the wellknown
DataGuide with (1) simultaneous keyword and path
matching and (2) a precomputed content/structure join. Extensive
experiments prove the CADG to be 50-90% faster
than the DataGuide for various sorts of query and document,
including difficult cases such as poorly structured
queries and recursive document paths. A new query classification
scheme identifies precise query characteristics with
a predominant influence on the performance of the individual
indices. The experiments show that the CADG is applicable
to many real-world applications, in particular large
collections of heterogeneously structured XML documents
Data-centric Misbehavior Detection in VANETs
Detecting misbehavior (such as transmissions of false information) in
vehicular ad hoc networks (VANETs) is very important problem with wide range of
implications including safety related and congestion avoidance applications. We
discuss several limitations of existing misbehavior detection schemes (MDS)
designed for VANETs. Most MDS are concerned with detection of malicious nodes.
In most situations, vehicles would send wrong information because of selfish
reasons of their owners, e.g. for gaining access to a particular lane. Because
of this (\emph{rational behavior}), it is more important to detect false
information than to identify misbehaving nodes. We introduce the concept of
data-centric misbehavior detection and propose algorithms which detect false
alert messages and misbehaving nodes by observing their actions after sending
out the alert messages. With the data-centric MDS, each node can independently
decide whether an information received is correct or false. The decision is
based on the consistency of recent messages and new alert with reported and
estimated vehicle positions. No voting or majority decisions is needed, making
our MDS resilient to Sybil attacks. Instead of revoking all the secret
credentials of misbehaving nodes, as done in most schemes, we impose fines on
misbehaving nodes (administered by the certification authority), discouraging
them to act selfishly. This reduces the computation and communication costs
involved in revoking all the secret credentials of misbehaving nodes.Comment: 12 page
- …