Supporting Regularized Logistic Regression Privately and Efficiently

As one of the most popular statistical and machine learning models, logistic regression with regularization has found wide adoption in biomedicine, social sciences, information technology, and so on. These domains often involve data of human subjects that are contingent upon strict privacy regulations. Increasing concerns over data privacy make it more and more difficult to coordinate and conduct large-scale collaborative studies, which typically rely on cross-institution data sharing and joint analysis. Our work here focuses on safeguarding regularized logistic regression, a widely-used machine learning model in various disciplines while at the same time has not been investigated from a data security and privacy perspective. We consider a common use scenario of multi-institution collaborative studies, such as in the form of research consortia or networks as widely seen in genetics, epidemiology, social sciences, etc. To make our privacy-enhancing solution practical, we demonstrate a non-conventional and computationally efficient method leveraging distributing computing and strong cryptography to provide comprehensive protection over individual-level and summary data. Extensive empirical evaluation on several studies validated the privacy guarantees, efficiency and scalability of our proposal. We also discuss the practical implications of our solution for large-scale studies and applications from various disciplines, including genetic and biomedical studies, smart grid, network analysis, etc

Identity in research infrastructure and scientific communication: Report from the 1st IRISC workshop, Helsinki Sep 12-13, 2011

Motivation for the IRISC workshop came from the observation that identity and digital identification are increasingly important factors in modern scientific research, especially with the now near-ubiquitous use of the Internet as a global medium for dissemination and debate of scientific knowledge and data, and as a platform for scientific collaborations and large-scale e-science activities.

The 1 1/2 day IRISC2011 workshop sought to explore a series of interrelated topics under two main themes: i) unambiguously identifying authors/creators & attributing their scholarly works, and ii) individual identification and access management in the context of identity federations. Specific aims of the workshop included:

• Raising overall awareness of key technical and non-technical challenges, opportunities and developments.
• Facilitating a dialogue, cross-pollination of ideas, collaboration and coordination between diverse – and largely unconnected – communities.
• Identifying & discussing existing/emerging technologies, best practices and requirements for researcher identification.

This report provides background information on key identification-related concepts & projects, describes workshop proceedings and summarizes key workshop findings

A conceptual model of enterprise application integration in higher education institutions

Copyright @ 2013 EMCIS.It is eminent that several applications’ systems are deployed at different levels in Higher Education (HE), ranging from academic and administrative to staff and students record systems. Many of these systems suffer from different problems due to the lack of integration such as data redundancy, inconsistency and maintenance cost. Enterprise Application Integration (EAI) can provide substantial benefits to these systems, such as assisting with business process integration, facilitating e-service based transformation and supporting collaborative decision-making. However, some factors that influence EAI adoption process in HE will be defined. This paper introduces a conceptual model to explain the outcome of using EAI in Higher Education Institutions (HEIs). Analyzing the combination of the existing classification of EAI factors with the HE factors will enhance the implementation of EAI in HEI at both organizational and operational levels. A pilot study at King Abdulaziz University (KAU), Kingdom of Saudi Arabia will be presented in this paper to show that the integration of the multiple information systems gives an integrated view to facilitate information access and reuse. Moreover data from different information systems is combined to gain a more comprehensive basis to satisfy the educational needs

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 district’s 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 district’s 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

User oriented access to secure biomedical resources through the grid

The life science domain is typified by heterogeneous data sets that are evolving at an exponential rate. Numerous post-genomic databases and areas of post-genomic life science research have been established and are being actively explored. Whilst many of these databases are public and freely accessible, it is often the case that researchers have data that is not so freely available and access to this data needs to be strictly controlled when distributed collaborative research is undertaken. Grid technologies provide one mechanism by which access to and integration of federated data sets is possible. Combining such data access and integration technologies with fine grained security infrastructures facilitates the establishment of virtual organisations (VO). However experience has shown that the general research (non-Grid) community are not comfortable with the Grid and its associated security models based upon public key infrastructures (PKIs). The Internet2 Shibboleth technology helps to overcome this through users only having to log in to their home site to gain access to resources across a VO – or in Shibboleth terminology a federation. In this paper we outline how we have applied the combination of Grid technologies, advanced security infrastructures and the Internet2 Shibboleth technology in several biomedical projects to provide a user-oriented model for secure access to and usage of Grid resources. We believe that this model may well become the de facto mechanism for undertaking e-Research on the Grid across numerous domains including the life sciences

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 district’s 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

Bridging the Data Divide: Understanding State Agency and University Research Partnerships within SLDS

This report examines this question through an analysis of state agency-university researcher partnerships that exist in State Longitudinal Data Systems (SLDS). Building state agency-university researcher partnerships is an important value of SLDS. To examine state agency-university researcher partnerships within SLDS, our analysis is guided by the following set of questions based on 71 interviews conducted with individuals most directly involved with SLDS efforts in Virginia, Maryland, Texas and Washington. The findings from this analysis suggest that each state’s SLDS organization and governance structure includes university partners in differing ways. In general, stronger partnership efforts are driven by legislative action or executive-level leadership. Regardless of structure, the operation of these partnerships is shaped by the agency’s previous experience and cultural norms surrounding the value and inclusion of university researchers