76,905 research outputs found

    Information Flow for Web Security and Privacy

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    The use of libraries is prevalent in modern web development. But how to ensure sensitive data is not being leaked through these libraries? This is the first challenge this thesis aims to solve. We propose the use of information-flow control by developing a principled approach to allow information-flow tracking in libraries, even if the libraries are written in a language not supporting information-flow control. The approach allows library functions to have unlabel\ua0and relabel models that explain how values are unlabeled and relabeled when marshaled between the labeled program and the unlabeled library. The approach handles primitive values and lists, records, higher-order functions, and references through the use of lazy marshaling.Web pages can combine benign properties of a user\u27s browser to a fingerprint, which can identify the user. Fingerprinting can be intrusive and often happens without the user\u27s consent. The second challenge this thesis aims to solve is to bridge the gap between the principled approach of handling libraries, to practical use in the information-flow aware JavaScript interpreter JSFlow. We extend JSFlow to handle libraries and be deployed in a browser, enabling information-flow tracking on web pages to detect fingerprinting.Modern browsers allow for browser modifications through browser\ua0extensions. These extensions can be intrusive by, e.g., blocking content ormodifying the DOM, and it can be in the interest of web pages to detect which extensions are installed in the browser. The third challenge this thesis aims to solve is finding which browser extensions are executing in a user\u27s browser, and investigate how the installed browser extensions can be used to decrease the privacy of users. We do this by conducting several large-scale studies and show that due to added security by browser vendors, a web page may uniquely identify a user based on the installed browser extension alone.It is popular to use filter lists to block unwanted content such as ads and tracking scripts on web pages. These filter lists are usually crowd-sourced andmainly focus on English speaking regions. Non-English speaking regions should use a supplementary filter list, but smaller linguistic regions may not have an up to date filter list. The fourth challenge this thesis aims to solve is how to automatically generate supplementary filter lists for regions which currently do not have an up to date filter list

    REDCap and DDI Exporting Data and Metadata with the API

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    Presentation at the North American Data Documentation Conference (NADDI) 2013The REDCap (Research Electronic Data Capture) consortium is a group of over 450 institutions that supports a web application which supports data capture for research studies (see http://project-redcap.org/). The application allows interactive survey instrument development and data collection. Data and scripts for SPSS, SAS and R can be exported from REDCap. Survey metadata including question text and flow control can be also exported as a csv file. This paper describes code in the R language to convert the REDCap survey metadata from csv to DDI 3.1. It includes a discussion of which REDCap instrument attributes can be represented by DDI 3.1 elements other than Note. This presentation includes information on the REDCap API and metadata about mapping data entry forms to events in a longitudinal study.Institute for Policy & Social Research, University of Kansas; University of Kansas Libraries; Alfred P. Sloan Foundation; Data Documentation Initiative Allianc

    Policy-agnostic programming on the client-side

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    Browser security has become a major concern especially due to web pages becoming more complex. These web applications handle a lot of information, including sensitive data that may be vulnerable to attacks like data exfiltration, cross-site scripting (XSS), etc. Most modern browsers have security mechanisms in place to prevent such attacks but they still fall short in preventing more advanced attacks like evolved variants of data exfiltration. Moreover, there is no standard that is followed to implement security into the browser. A lot of research has been done in the field of information flow security that could prove to be helpful in solving the problem of securing the client-side. Policy- agnostic programming is a programming paradigm that aims to make implementation of information flow security in real world systems more flexible. In this paper, we explore the use of policy-agnostic programming on the client-side and how it will help prevent common client-side attacks. We verify our results through a client-side salary management application. We show a possible attack and how our solution would prevent such an attack

    The Web SSO Standard OpenID Connect: In-Depth Formal Security Analysis and Security Guidelines

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    Web-based single sign-on (SSO) services such as Google Sign-In and Log In with Paypal are based on the OpenID Connect protocol. This protocol enables so-called relying parties to delegate user authentication to so-called identity providers. OpenID Connect is one of the newest and most widely deployed single sign-on protocols on the web. Despite its importance, it has not received much attention from security researchers so far, and in particular, has not undergone any rigorous security analysis. In this paper, we carry out the first in-depth security analysis of OpenID Connect. To this end, we use a comprehensive generic model of the web to develop a detailed formal model of OpenID Connect. Based on this model, we then precisely formalize and prove central security properties for OpenID Connect, including authentication, authorization, and session integrity properties. In our modeling of OpenID Connect, we employ security measures in order to avoid attacks on OpenID Connect that have been discovered previously and new attack variants that we document for the first time in this paper. Based on these security measures, we propose security guidelines for implementors of OpenID Connect. Our formal analysis demonstrates that these guidelines are in fact effective and sufficient.Comment: An abridged version appears in CSF 2017. Parts of this work extend the web model presented in arXiv:1411.7210, arXiv:1403.1866, arXiv:1508.01719, and arXiv:1601.0122

    Multiplierz: An Extensible API Based Desktop Environment for Proteomics Data Analysis

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    BACKGROUND. Efficient analysis of results from mass spectrometry-based proteomics experiments requires access to disparate data types, including native mass spectrometry files, output from algorithms that assign peptide sequence to MS/MS spectra, and annotation for proteins and pathways from various database sources. Moreover, proteomics technologies and experimental methods are not yet standardized; hence a high degree of flexibility is necessary for efficient support of high- and low-throughput data analytic tasks. Development of a desktop environment that is sufficiently robust for deployment in data analytic pipelines, and simultaneously supports customization for programmers and non-programmers alike, has proven to be a significant challenge. RESULTS. We describe multiplierz, a flexible and open-source desktop environment for comprehensive proteomics data analysis. We use this framework to expose a prototype version of our recently proposed common API (mzAPI) designed for direct access to proprietary mass spectrometry files. In addition to routine data analytic tasks, multiplierz supports generation of information rich, portable spreadsheet-based reports. Moreover, multiplierz is designed around a "zero infrastructure" philosophy, meaning that it can be deployed by end users with little or no system administration support. Finally, access to multiplierz functionality is provided via high-level Python scripts, resulting in a fully extensible data analytic environment for rapid development of custom algorithms and deployment of high-throughput data pipelines. CONCLUSION. Collectively, mzAPI and multiplierz facilitate a wide range of data analysis tasks, spanning technology development to biological annotation, for mass spectrometry-based proteomics research.Dana-Farber Cancer Institute; National Human Genome Research Institute (P50HG004233); National Science Foundation Integrative Graduate Education and Research Traineeship grant (DGE-0654108
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