A Comparative Forensic Analysis of Privacy Enhanced Web Browsers Ryan M
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Google Docs Accessibility (Pdf)
Google Docs Accessibility (A11y) Building Accessible Google Docs • Heading Styles • Images • Table of Contents • Captioning • Columns and Lists • Tables A11y • Tab Stops • Color Contrast • Paragraph Spacing • Headers and Footers • Meaningful Link Text • Accessibility Checker What is Assistive Technology? Assistive Technology (AT) are “products, equipment, and systems that enhance learning, working, and daily living for persons with disabilities.” Magnification Speech Screen Readers Software Recognition Trackball Mouse Keyboard Zoom Text Braille Computer Keyboard Captions/Subtitles Captioned Telephone Video Relay Services Captioning Videos Per federal and state law, and CSU policy, instructional media (e.g., videos, captured lectures, recorded presentations) must have captions. This includes instructional media used in classrooms, posted on websites or shared in Canvas. • All students who are enrolled in a course must be able to access the content in the course. • Faculty: Funding is available to help faculty generate captions and transcripts for instructional media. Materials should be submitted at least six weeks in advance of their use in instruction. • Staff: For CSUN staff who do not provide classroom material, there is a cost through chargeback. For information on the chargeback, email [email protected]. csun.edu/captioning What are Screen Readers Screen readers are a form of assistive technology (AT) software that enables access to a computer, and all the things a computer does, by attempting to identify and interpret what is being displayed on the computer screen using text-to-speech. Screen readers can only access and process live text (fully editable or selectable text). • Provides access to someone who is visually impaired, mobility or has a learning disability to access text on the screen. -
A Generic Data Exchange System for F2F Networks
The Retroshare project The GXS system Decentralize your app! A Generic Data Exchange System for F2F Networks Cyril Soler C.Soler The GXS System 03 Feb. 2018 1 / 19 The Retroshare project The GXS system Decentralize your app! Outline I Overview of Retroshare I The GXS system I Decentralize your app! C.Soler The GXS System 03 Feb. 2018 2 / 19 The Retroshare project The GXS system Decentralize your app! The Retroshare Project I Mesh computers using signed TLS over TCP/UDP/Tor/I2P; I anonymous end-to-end encrypted FT with swarming; I mail, IRC chat, forums, channels; I available on Mac OS, Linux, Windows, (+ Android). C.Soler The GXS System 03 Feb. 2018 3 / 19 The Retroshare project The GXS system Decentralize your app! The Retroshare Project I Mesh computers using signed TLS over TCP/UDP/Tor/I2P; I anonymous end-to-end encrypted FT with swarming; I mail, IRC chat, forums, channels; I available on Mac OS, Linux, Windows. C.Soler The GXS System 03 Feb. 2018 3 / 19 The Retroshare project The GXS system Decentralize your app! The Retroshare Project I Mesh computers using signed TLS over TCP/UDP/Tor/I2P; I anonymous end-to-end encrypted FT with swarming; I mail, IRC chat, forums, channels; I available on Mac OS, Linux, Windows. C.Soler The GXS System 03 Feb. 2018 3 / 19 The Retroshare project The GXS system Decentralize your app! The Retroshare Project I Mesh computers using signed TLS over TCP/UDP/Tor/I2P; I anonymous end-to-end encrypted FT with swarming; I mail, IRC chat, forums, channels; I available on Mac OS, Linux, Windows. -
Anonymous Rate Limiting with Direct Anonymous Attestation
Anonymous rate limiting with Direct Anonymous Attestation Alex Catarineu Philipp Claßen Cliqz GmbH, Munich Konark Modi Josep M. Pujol 25.09.18 Crypto and Privacy Village 2018 Data is essential to build services 25.09.18 Crypto and Privacy Village 2018 Problems with Data Collection IP UA Timestamp Message Payload Cookie Type 195.202.XX.XX FF.. 2018-07-09 QueryLog [face, facebook.com] Cookie=966347bfd 14:01 1e550 195.202.XX.XX Chrome.. 2018-07-09 Page https://analytics.twitter.com/user/konark Cookie=966347bfd 14:06 modi 1e55040434abe… 195.202.XX.XX Chrome.. 2018-07-09 QueryLog [face, facebook.com] Cookie=966347bfd 14:10 1e55040434abe… 195.202.XX.XX Chrome.. 2018-07-09 Page https://booking.com/hotels/barcelona Cookie=966347bfd 16:15 1e55040434abe… 195.202.XX.XX Chrome.. 2018-07-09 QueryLog [face, facebook.com] Cookie=966347bfd 14:10 1e55040434abe… 195.202.XX.XX FF.. 2018-07-09 Page https://shop.flixbus.de/user/resetting/res Cookie=966347bfd 18:40 et/hi7KTb1Pxa4lXqKMcwLXC0XzN- 1e55040434abe… 47Tt0Q 25.09.18 Crypto and Privacy Village 2018 Anonymous data collection Timestamp Message Type Payload 2018-07-09 14 Querylog [face, facebook.com] 2018-07-09 14 Querylog [boo, booking.com] 2018-07-09 14 Page https://booking.com/hotels/barcelona 2018-07-09 14 Telemetry [‘engagement’: 0 page loads last week, 5023 page loads last month] More details: https://gist.github.com/solso/423a1104a9e3c1e3b8d7c9ca14e885e5 http://josepmpujol.net/public/papers/big_green_tracker.pdf 25.09.18 Crypto and Privacy Village 2018 Motivation: Preventing attacks on anonymous data collection Timestamp Message Type Payload 2018-07-09 14 querylog [book, booking.com] 2018-07-09 14 querylog [fac, facebook.com] … …. -
Private Browsing
Away From Prying Eyes: Analyzing Usage and Understanding of Private Browsing Hana Habib, Jessica Colnago, Vidya Gopalakrishnan, Sarah Pearman, Jeremy Thomas, Alessandro Acquisti, Nicolas Christin, and Lorrie Faith Cranor, Carnegie Mellon University https://www.usenix.org/conference/soups2018/presentation/habib-prying This paper is included in the Proceedings of the Fourteenth Symposium on Usable Privacy and Security. August 12–14, 2018 • Baltimore, MD, USA ISBN 978-1-939133-10-6 Open access to the Proceedings of the Fourteenth Symposium on Usable Privacy and Security is sponsored by USENIX. Away From Prying Eyes: Analyzing Usage and Understanding of Private Browsing Hana Habib, Jessica Colnago, Vidya Gopalakrishnan, Sarah Pearman, Jeremy Thomas, Alessandro Acquisti, Nicolas Christin, Lorrie Faith Cranor Carnegie Mellon University {htq, jcolnago, vidyag, spearman, thomasjm, acquisti, nicolasc, lorrie}@andrew.cmu.edu ABSTRACT Prior user studies have examined different aspects of private Previous research has suggested that people use the private browsing, including contexts for using private browsing [4, browsing mode of their web browsers to conduct privacy- 10, 16, 28, 41], general misconceptions of how private brows- sensitive activities online, but have misconceptions about ing technically functions and the protections it offers [10,16], how it works and are likely to overestimate the protections and usability issues with private browsing interfaces [41,44]. it provides. To better understand how private browsing is A major limitation of much prior work is that it is based used and whether users are at risk, we analyzed browsing on self-reported survey data, which may not always be reli- data collected from over 450 participants of the Security able. -
Profiles Research Networking Software Installation Guide
Profiles Research Networking Software Installation Guide Documentation Version : July 25, 2014 Software Version : ProfilesRNS_2.1.0 Table of Contents Introduction ..................................................................................................................... 2 Hardware and Operating System Requirements ............................................................. 3 Download Options ........................................................................................................... 4 Installing the Database .................................................................................................... 5 Loading Person Data....................................................................................................... 8 Loading Person Data: Part 1 – Importing SSIS Packages into SQL Server msdb Database ..................................................................................................................... 8 Loading Person Data: Part 2 – Importing Demographic Data .................................... 10 Loading Person Data: Part 3 – Geocoding ................................................................ 15 Loading Person Data: Part 4 – Obtaining Publications .............................................. 16 Loading Person Data: Part 5 – Convert data to RDF ................................................. 19 Scheduling Database Jobs ............................................................................................ 21 Installing the Code........................................................................................................ -
HTTP Cookie - Wikipedia, the Free Encyclopedia 14/05/2014
HTTP cookie - Wikipedia, the free encyclopedia 14/05/2014 Create account Log in Article Talk Read Edit View history Search HTTP cookie From Wikipedia, the free encyclopedia Navigation A cookie, also known as an HTTP cookie, web cookie, or browser HTTP Main page cookie, is a small piece of data sent from a website and stored in a Persistence · Compression · HTTPS · Contents user's web browser while the user is browsing that website. Every time Request methods Featured content the user loads the website, the browser sends the cookie back to the OPTIONS · GET · HEAD · POST · PUT · Current events server to notify the website of the user's previous activity.[1] Cookies DELETE · TRACE · CONNECT · PATCH · Random article Donate to Wikipedia were designed to be a reliable mechanism for websites to remember Header fields Wikimedia Shop stateful information (such as items in a shopping cart) or to record the Cookie · ETag · Location · HTTP referer · DNT user's browsing activity (including clicking particular buttons, logging in, · X-Forwarded-For · Interaction or recording which pages were visited by the user as far back as months Status codes or years ago). 301 Moved Permanently · 302 Found · Help 303 See Other · 403 Forbidden · About Wikipedia Although cookies cannot carry viruses, and cannot install malware on 404 Not Found · [2] Community portal the host computer, tracking cookies and especially third-party v · t · e · Recent changes tracking cookies are commonly used as ways to compile long-term Contact page records of individuals' browsing histories—a potential privacy concern that prompted European[3] and U.S. -
A Comparison of Natural Language Understanding Platforms for Chatbots in Software Engineering
1 A Comparison of Natural Language Understanding Platforms for Chatbots in Software Engineering Ahmad Abdellatif, Khaled Badran, Diego Elias Costa, and Emad Shihab, Senior Member, IEEE Abstract—Chatbots are envisioned to dramatically change the future of Software Engineering, allowing practitioners to chat and inquire about their software projects and interact with different services using natural language. At the heart of every chatbot is a Natural Language Understanding (NLU) component that enables the chatbot to understand natural language input. Recently, many NLU platforms were provided to serve as an off-the-shelf NLU component for chatbots, however, selecting the best NLU for Software Engineering chatbots remains an open challenge. Therefore, in this paper, we evaluate four of the most commonly used NLUs, namely IBM Watson, Google Dialogflow, Rasa, and Microsoft LUIS to shed light on which NLU should be used in Software Engineering based chatbots. Specifically, we examine the NLUs’ performance in classifying intents, confidence scores stability, and extracting entities. To evaluate the NLUs, we use two datasets that reflect two common tasks performed by Software Engineering practitioners, 1) the task of chatting with the chatbot to ask questions about software repositories 2) the task of asking development questions on Q&A forums (e.g., Stack Overflow). According to our findings, IBM Watson is the best performing NLU when considering the three aspects (intents classification, confidence scores, and entity extraction). However, the results from each individual aspect show that, in intents classification, IBM Watson performs the best with an F1-measure>84%, but in confidence scores, Rasa comes on top with a median confidence score higher than 0.91. -
Connected Cl As Sroom
Data in the Cloud he ability to move from one representation monthly temperatures for cities in the United of data to another is one of the key char- States, South America, and Russia. Tacteristics of expert mathematicians and A quick inspection of the graph makes it evi- scientists. Cloud computing will offer more dent that on average it is always colder in Verk- opportunities to create and display multiple hoyansk than in Washington (and much colder representations of data, making this skill in the winter) and that the seasons in the south- even more important in the future. ern hemisphere are reversed. These patterns would have been much more difficult to discern Multiple Representations in a table of numbers alone. We can represent data in a variety of forms— Even young students can explore multiple rep- graphs, charts, tables of numbers, equations. resentations of the same data with software such Mathematicians, scientists, and engineers often as The Graph Club (Tom Snyder Productions). look for patterns in data. Different representations This application allows students to view two of the same data sometimes make it easier to see linked representations of data simultaneously. As a pattern. For example, the pattern in the table children drag icons to form a picture graph or of numbers below is not immediately evident. enter numbers in a simple table, a corresponding bar graph or pie chart takes shape (see Figure 2). Changing the size of a sector in the circle graph or the height of a bar in a bar chart Table 1. changes the pictogram or vice versa. -
DARK WEB INVESTIGATION GUIDE Contents 1
DARK WEB INVESTIGATION GUIDE Contents 1. Introduction 3 2. Setting up Chrome for Dark Web Access 5 3. Setting up Virtual Machines for Dark Web Access 9 4. Starting Points for Tor Investigations 20 5. Technical Clues for De-Anonymizing Hidden Services 22 5.1 Censys.io SSL Certificates 23 5.2 Searching Shodan for Hidden Services 24 5.3 Checking an IP Address for Tor Usage 24 5.4 Additional Resources 25 6. Conclusion 26 2 Dark Web Investigation Guide 1 1. Introduction 3 Introduction 1 There is a lot of confusion about what the dark web is vs. the deep web. The dark web is part of the Internet that is not accessible through traditional means. It requires that you use a technology like Tor (The Onion Router) or I2P (Invisible Internet Project) in order to access websites, email or other services. The deep web is slightly different. The deep web is made of all the webpages or entire websites that have not been crawled by a search engine. This could be because they are hidden behind paywalls or require a username and password to access. We are going to be setting up access to the dark web with a focus on the Tor network. We are going to accomplish this in two different ways. The first way is to use the Tor Browser to get Google Chrome connected to the the Tor network. This is the less private and secure option, but it is the easiest to set up and use and is sufficient for accessing material on the dark web. -
Forensic Study and Analysis of Different Artifacts of Web Browsers in Private Browsing Mode
|| Volume 5 || Issue 6 || June 2020 || ISSN (Online) 2456-0774 INTERNATIONAL JOURNAL OF ADVANCE SCIENTIFIC RESEARCH AND ENGINEERING TRENDS FORENSIC STUDY AND ANALYSIS OF DIFFERENT ARTIFACTS OF WEB BROWSERS IN PRIVATE BROWSING MODE Rinchon Sanghkroo1, Dr. Deepak Raj Rao G.2 and Kumarshankar Raychaudhuri3 M.Sc. (Forensic Science) Final Semester Student, Cyber Forensic Division, LNJN National Institute of Criminology and Forensic Science (MHA), Delhi, India 1 Assistant Professor, Cyber Forensic Division, LNJN National Institute of Criminology and Forensic Science (MHA), Delhi, India2 Junior Research Fellow, Cyber Forensic Division, LNJN National Institute of Criminology and Forensic Science (MHA), Delhi, India3 [email protected], [email protected], [email protected] ------------------------------------------------------ ***-------------------------------------------------- Abstract: - Web browsers today have become one of the most commonly used applications in digital devices, storing and maintaining huge information on user activities. The privacy mode has been introduced to combat the privacy issues related with browsers. This feature keeps the browsing activities of a user private by not storing or removing the traces of artifacts related to the browsing session on the system. In this study, we test the effectiveness of this claim and to ensure ways in which a forensic investigation may be done in such cases. The private modes of different browsers have been tested in Windows and MAC OS by performing pre-defined browsing activities in each of the browsers in both the operating systems. Moreover, the default locations of normal web browser artifacts are also examined to find whether artifacts of private browsing activities are stored in such locations or not. Keywords: - Private Browsing, Windows, MAC, Safari, Microsoft Edge, Brave Browser ------------------------------------------------------ ***-------------------------------------------------- I INTRODUCTON artifacts related to it on the end device. -
Tracking Users Across the Web Via TLS Session Resumption
Tracking Users across the Web via TLS Session Resumption Erik Sy Christian Burkert University of Hamburg University of Hamburg Hannes Federrath Mathias Fischer University of Hamburg University of Hamburg ABSTRACT modes, and browser extensions to restrict tracking practices such as User tracking on the Internet can come in various forms, e.g., via HTTP cookies. Browser fingerprinting got more difficult, as trackers cookies or by fingerprinting web browsers. A technique that got can hardly distinguish the fingerprints of mobile browsers. They are less attention so far is user tracking based on TLS and specifically often not as unique as their counterparts on desktop systems [4, 12]. based on the TLS session resumption mechanism. To the best of Tracking based on IP addresses is restricted because of NAT that our knowledge, we are the first that investigate the applicability of causes users to share public IP addresses and it cannot track devices TLS session resumption for user tracking. For that, we evaluated across different networks. As a result, trackers have an increased the configuration of 48 popular browsers and one million of the interest in additional methods for regaining the visibility on the most popular websites. Moreover, we present a so-called prolon- browsing habits of users. The result is a race of arms between gation attack, which allows extending the tracking period beyond trackers as well as privacy-aware users and browser vendors. the lifetime of the session resumption mechanism. To show that One novel tracking technique could be based on TLS session re- under the observed browser configurations tracking via TLS session sumption, which allows abbreviating TLS handshakes by leveraging resumptions is feasible, we also looked into DNS data to understand key material exchanged in an earlier TLS session. -
Forensic Investigation of User's Web Activity on Google Chrome Using
IJCSNS International Journal of Computer Science and Network Security, VOL.16 No.9, September 2016 123 Forensic Investigation of User’s Web Activity on Google Chrome using various Forensic Tools Narmeen Shafqat, NUST, Pakistan Summary acknowledged browsers like Internet Explorer, Google Cyber Crimes are increasing day by day, ranging from Chrome, Mozilla Firefox, Safari, Opera etc. but should confidentiality violation to identity theft and much more. The also have hands on experience of less popular web web activity of the suspect, whether carried out on computer or browsers like Erwise, Arena, Cello, Netscape, iCab, smart device, is hence of particular interest to the forensics Cyberdog etc. Not only this, the forensic experts should investigator. Browser forensics i.e forensics of suspect’s browser also know how to find artifacts of interest from older history, saved passwords, cache, recent tabs opened etc. , therefore supply ample amount of information to the forensic versions of well-known web browsers; Internet Explorer, experts in case of any illegal involvement of the culprit in any Chrome and Mozilla Firefox atleast, because he might activity done on web browsers. Owing to the growing popularity experience a case where the suspected person is using and widespread use of the Google Chrome web browser, this older versions of these browsers. paper will forensically analyse the said browser in windows 8 According to StatCounter Global market share for the web environment, using various forensics tools and techniques, with browsers (2015), Google Chrome, Mozilla Firefox and the aim to reconstruct the web browsing activities of the suspect. Microsoft’s Internet Explorer make up 90% of the browser The working of Google Chrome in regular mode, private usage.