10,394 research outputs found
A Web-Based Tool for Analysing Normative Documents in English
Our goal is to use formal methods to analyse normative documents written in
English, such as privacy policies and service-level agreements. This requires
the combination of a number of different elements, including information
extraction from natural language, formal languages for model representation,
and an interface for property specification and verification. We have worked on
a collection of components for this task: a natural language extraction tool, a
suitable formalism for representing such documents, an interface for building
models in this formalism, and methods for answering queries asked of a given
model. In this work, each of these concerns is brought together in a web-based
tool, providing a single interface for analysing normative texts in English.
Through the use of a running example, we describe each component and
demonstrate the workflow established by our tool
Authorised Translations of Electronic Documents
A concept is proposed to extend authorised translations of documents to
electronically signed, digital documents. Central element of the solution is an
electronic seal, embodied as an XML data structure, which attests to the
correctness of the translation and the authorisation of the translator. The
seal contains a digital signature binding together original and translated
document, thus enabling forensic inspection and therefore legal security in the
appropriation of the translation. Organisational aspects of possible
implementation variants of electronic authorised translations are discussed and
a realisation as a stand-alone web-service is presented.Comment: In: Peer-reviewed Proceedings of the Information Security South
Africa (ISSA) 2006 From Insight to Foresight Conference, 5 to 7 July 2006,
Sandton, South Afric
Recovering Residual Forensic Data from Smartphone Interactions with Cloud Storage Providers
There is a growing demand for cloud storage services such as Dropbox, Box,
Syncplicity and SugarSync. These public cloud storage services can store
gigabytes of corporate and personal data in remote data centres around the
world, which can then be synchronized to multiple devices. This creates an
environment which is potentially conducive to security incidents, data breaches
and other malicious activities. The forensic investigation of public cloud
environments presents a number of new challenges for the digital forensics
community. However, it is anticipated that end-devices such as smartphones,
will retain data from these cloud storage services. This research investigates
how forensic tools that are currently available to practitioners can be used to
provide a practical solution for the problems related to investigating cloud
storage environments. The research contribution is threefold. First, the
findings from this research support the idea that end-devices which have been
used to access cloud storage services can be used to provide a partial view of
the evidence stored in the cloud service. Second, the research provides a
comparison of the number of files which can be recovered from different
versions of cloud storage applications. In doing so, it also supports the idea
that amalgamating the files recovered from more than one device can result in
the recovery of a more complete dataset. Third, the chapter contributes to the
documentation and evidentiary discussion of the artefacts created from specific
cloud storage applications and different versions of these applications on iOS
and Android smartphones
IVOA Recommendation: Simple Spectral Access Protocol Version 1.1
The Simple Spectral Access (SSA) Protocol (SSAP) defines a uniform interface
to remotely discover and access one dimensional spectra. SSA is a member of an
integrated family of data access interfaces altogether comprising the Data
Access Layer (DAL) of the IVOA. SSA is based on a more general data model
capable of describing most tabular spectrophotometric data, including time
series and spectral energy distributions (SEDs) as well as 1-D spectra; however
the scope of the SSA interface as specified in this document is limited to
simple 1-D spectra, including simple aggregations of 1-D spectra. The form of
the SSA interface is simple: clients first query the global resource registry
to find services of interest and then issue a data discovery query to selected
services to determine what relevant data is available from each service; the
candidate datasets available are described uniformly in a VOTable format
document which is returned in response to the query. Finally, the client may
retrieve selected datasets for analysis. Spectrum datasets returned by an SSA
spectrum service may be either precomputed, archival datasets, or they may be
virtual data which is computed on the fly to respond to a client request.
Spectrum datasets may conform to a standard data model defined by SSA, or may
be native spectra with custom project-defined content. Spectra may be returned
in any of a number of standard data formats. Spectral data is generally stored
externally to the VO in a format specific to each spectral data collection;
currently there is no standard way to represent astronomical spectra, and
virtually every project does it differently. Hence spectra may be actively
mediated to the standard SSA-defined data model at access time by the service,
so that client analysis programs do not have to be familiar with the
idiosyncratic details of each data collection to be accessed
Database independent Migration of Objects into an Object-Relational Database
This paper reports on the CERN-based WISDOM project which is studying the
serialisation and deserialisation of data to/from an object database
(objectivity) and ORACLE 9i.Comment: 26 pages, 18 figures; CMS CERN Conference Report cr02_01
Methodologies for the Automatic Location of Academic and Educational Texts on the Internet
Traditionally online databases of web resources have been compiled by a human editor, or though the submissions of authors or interested parties. Considerable resources are needed to maintain a constant level of input and relevance in the face of increasing material quantity and quality, and much of what is in databases is of an ephemeral nature. These pressures dictate that many databases stagnate after an initial period of enthusiastic data entry. The solution to this problem would seem to be the automatic harvesting of resources, however, this process necessitates the automatic classification of resources as ‘appropriate’ to a given database, a problem only solved by complex text content analysis.
This paper outlines the component methodologies necessary to construct such an automated harvesting system, including a number of novel approaches. In particular this paper looks at the specific problems of automatically identifying academic research work and Higher Education pedagogic materials. Where appropriate, experimental data is presented from searches in the field of Geography as well as the Earth and Environmental Sciences. In addition, appropriate software is reviewed where it exists, and future directions are outlined
Methodologies for the Automatic Location of Academic and Educational Texts on the Internet
Traditionally online databases of web resources have been compiled by a human editor, or though the submissions of authors or interested parties. Considerable resources are needed to maintain a constant level of input and relevance in the face of increasing material quantity and quality, and much of what is in databases is of an ephemeral nature. These pressures dictate that many databases stagnate after an initial period of enthusiastic data entry. The solution to this problem would seem to be the automatic harvesting of resources, however, this process necessitates the automatic classification of resources as ‘appropriate’ to a given database, a problem only solved by complex text content analysis.
This paper outlines the component methodologies necessary to construct such an automated harvesting system, including a number of novel approaches. In particular this paper looks at the specific problems of automatically identifying academic research work and Higher Education pedagogic materials. Where appropriate, experimental data is presented from searches in the field of Geography as well as the Earth and Environmental Sciences. In addition, appropriate software is reviewed where it exists, and future directions are outlined
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