340,981 research outputs found
WARP: A ICN architecture for social data
Social network companies maintain complete visibility and ownership of the
data they store. However users should be able to maintain full control over
their content. For this purpose, we propose WARP, an architecture based upon
Information-Centric Networking (ICN) designs, which expands the scope of the
ICN architecture beyond media distribution, to provide data control in social
networks. The benefit of our solution lies in the lightweight nature of the
protocol and in its layered design. With WARP, data distribution and access
policies are enforced on the user side. Data can still be replicated in an ICN
fashion but we introduce control channels, named \textit{thread updates}, which
ensures that the access to the data is always updated to the latest control
policy. WARP decentralizes the social network but still offers APIs so that
social network providers can build products and business models on top of WARP.
Social applications run directly on the user's device and store their data on
the user's \textit{butler} that takes care of encryption and distribution.
Moreover, users can still rely on third parties to have high-availability
without renouncing their privacy
A User-Focused Reference Model for Wireless Systems Beyond 3G
This whitepaper describes a proposal from Working Group 1, the Human Perspective of the Wireless World, for a user-focused reference model for systems beyond 3G. The general structure of the proposed model involves two "planes": the Value Plane and the Capability Plane. The characteristics of these planes are discussed in detail and an example application of the model to a specific scenario for the wireless world is provided
Quantum surveillance and 'shared secrets'. A biometric step too far? CEPS Liberty and Security in Europe, July 2010
It is no longer sensible to regard biometrics as having neutral socio-economic, legal and political impacts. Newer generation biometrics are fluid and include behavioural and emotional data that can be combined with other data. Therefore, a range of issues needs to be reviewed in light of the increasing privatisation of âsecurityâ that escapes effective, democratic parliamentary and regulatory control and oversight at national, international and EU levels, argues Juliet Lodge, Professor and co-Director of the Jean Monnet European Centre of Excellence at the University of Leeds, U
Making GDPR Usable: A Model to Support Usability Evaluations of Privacy
We introduce a new model for evaluating privacy that builds on the criteria
proposed by the EuroPriSe certification scheme by adding usability criteria.
Our model is visually represented through a cube, called Usable Privacy Cube
(or UP Cube), where each of its three axes of variability captures,
respectively: rights of the data subjects, privacy principles, and usable
privacy criteria. We slightly reorganize the criteria of EuroPriSe to fit with
the UP Cube model, i.e., we show how EuroPriSe can be viewed as a combination
of only rights and principles, forming the two axes at the basis of our UP
Cube. In this way we also want to bring out two perspectives on privacy: that
of the data subjects and, respectively, that of the controllers/processors. We
define usable privacy criteria based on usability goals that we have extracted
from the whole text of the General Data Protection Regulation. The criteria are
designed to produce measurements of the level of usability with which the goals
are reached. Precisely, we measure effectiveness, efficiency, and satisfaction,
considering both the objective and the perceived usability outcomes, producing
measures of accuracy and completeness, of resource utilization (e.g., time,
effort, financial), and measures resulting from satisfaction scales. In the
long run, the UP Cube is meant to be the model behind a new certification
methodology capable of evaluating the usability of privacy, to the benefit of
common users. For industries, considering also the usability of privacy would
allow for greater business differentiation, beyond GDPR compliance.Comment: 41 pages, 2 figures, 1 table, and appendixe
Privacy and Cloud Computing in Public Schools
Today, data driven decision-making is at the center of educational policy debates in the United States. School districts are increasingly turning to rapidly evolving technologies and cloud computing to satisfy their educational objectives and take advantage of new opportunities for cost savings, flexibility, and always-available service among others. As public schools in the United States rapidly adopt cloud-computing services, and consequently transfer increasing quantities of student information to third-party providers, privacy issues become more salient and contentious. The protection of student privacy in the context of cloud computing is generally unknown both to the public and to policy-makers. This study thus focuses on K-12 public education and examines how school districts address privacy when they transfer student information to cloud computing service providers. The goals of the study are threefold: first, to provide a national picture of cloud computing in public schools; second, to assess how public schools address their statutory obligations as well as generally accepted privacy principles in their cloud service agreements; and, third, to make recommendations based on the findings to improve the protection of student privacy in the context of cloud computing. Fordham CLIP selected a national sample of school districts including large, medium and small school systems from every geographic region of the country. Using state open public record laws, Fordham CLIP requested from each selected district all of the districtâs cloud service agreements, notices to parents, and computer use policies for teachers. All of the materials were then coded against a checklist of legal obligations and privacy norms. The purpose for this coding was to enable a general assessment and was not designed to provide a compliance audit of any school district nor of any particular vendor.https://ir.lawnet.fordham.edu/clip/1001/thumbnail.jp
Privacy and Cloud Computing in Public Schools
Today, data driven decision-making is at the center of educational policy debates in the United States. School districts are increasingly turning to rapidly evolving technologies and cloud computing to satisfy their educational objectives and take advantage of new opportunities for cost savings, flexibility, and always-available service among others. As public schools in the United States rapidly adopt cloud-computing services, and consequently transfer increasing quantities of student information to third-party providers, privacy issues become more salient and contentious. The protection of student privacy in the context of cloud computing is generally unknown both to the public and to policy-makers. This study thus focuses on K-12 public education and examines how school districts address privacy when they transfer student information to cloud computing service providers. The goals of the study are threefold: first, to provide a national picture of cloud computing in public schools; second, to assess how public schools address their statutory obligations as well as generally accepted privacy principles in their cloud service agreements; and, third, to make recommendations based on the findings to improve the protection of student privacy in the context of cloud computing. Fordham CLIP selected a national sample of school districts including large, medium and small school systems from every geographic region of the country. Using state open public record laws, Fordham CLIP requested from each selected district all of the districtâs cloud service agreements, notices to parents, and computer use policies for teachers. All of the materials were then coded against a checklist of legal obligations and privacy norms. The purpose for this coding was to enable a general assessment and was not designed to provide a compliance audit of any school district nor of any particular vendor.https://ir.lawnet.fordham.edu/clip/1001/thumbnail.jp
- âŠ