PPT-Need for Privacy Enhancing Technologies

1 What is challenging about standard encryption Challenge Privacy versus Data Utilization Dilemma   Client Storage on the cloud Sensitive data Outsource the data SEARCH ANALYZE . Elaine Shi. Lecture 2 Attack. slides partially borrowed from Narayanan, Golle and Partridge . 2. The uniqueness of high-dimensional data. In this class:. . How many . male. :. . . How many . 1st year.  . אהרון . האופטמן. היחידה לחיזוי טכנולוגי וחברתי, אוניברסיטת ת"א. haupt@post.tau.ac.il www.notes.co.il/hauptman . Not predicting a pre-determined future, but exploring . Elaine Shi. Lecture 3 . Differential Privacy. Some slides adapted from Adam . Smith. ’. s . lecture and other talk slides. Roadmap. Defining Differential Privacy. Techniques for Achieving DP. Output perturbation. Elaine Shi. Lecture 1 . . Landscape. Privacy Definitions and Landscape, Attacks against Privacy. What Is Privacy?. Non-Privacy. Non-Privacy. Collecting information unbeknownst to users. Sell/share users’ information to third-parties violating contracts/terms-of-use/expectations. Elaine Shi. Lecture 4 Principles of System Security. slides partially borrowed from Jonathan Katz. Roadmap. Privacy and . System Security. Principle of least privilege. Principle of Privilege Separation. Elaine Shi. Lecture . 5 . Trusted Computing. Roadmap. Background on Trusted Computing. Whole-system, load-time attestation. Fine-grained, run-time attestation. or verifiable program execution. Trusted Computing & TPM. Carmela . Troncoso. , . Gradiant. PRIPARE Workshop on Privacy by Design. Ulm 9. th. -10. th. March 2015. 11/03/2015. 1. Privacy Enhancing Technologies. Outline. What are privacy enhancing technologies?. Learning. Charis Thompson. Chancellor’s Professor, UC Berkeley . Professor, . LSE. ABSTRACT and stakes. In this talk I review some of the biggest threats - for example, algorithmic oppression and triage, exacerbation of bubble chambers and inequality, and cybersecurity and autonomous weapons - and some of the biggest opportunities of the current state of machine learning, and consider the major approaches being taken to guiding machine learning for human benefit.  I then describe three initiatives we are pursuing to intervene, implement, and archive better practice. I. oT-based . P. rivacy-. P. reserving . PER. vasive . S. paces). Alfred Kobsa, Sharad Mehrotra, Nalini Venkatasubramanian. University of California Irvine. Raj Rajgopalan. Honeywell Research. a large team of TIPPERS researchers & developers at UCI Honeywell. Speaker Series. January 28, 2015 . Innovative Technologies to Increase Privacy. Dial-in: 1-855-767-1051 and Conference ID: 34619328. Administrative Items. Do not use your computer microphone to participate in this meeting. Lync will be used only as a display. Please dial in using the following information. Mobile Device Power Analysis. Yan . Michalevsky. , Aaron Schulman, . Gunaa. . Arumugam. . Veerapandian. , Dan . Boneh. , and Gabi . Nakibly. , USENIX Security, 2015. Presented by : Sintayehu Garedew. Digital Governance … … and Algorithms Law and Ethics for Disruptive Technologies Alan Charles Raul March 14 , 2019 Key Themes Shifting zeitgeist . High-profile data breaches, recent controversies concerning personal data (e.g., -researchcomThis publication should not be seen as an inducement under MiFID II regulationsPlease refer to important disclosures at the end of the document7 July2020KAPE TECHNOLOGIESSOFTWARE AND COMPU University. 2016 Digital Information Policy Scholars Conference on Privacy. George Mason University. The Economics of Privacy. “. The Economics of Privacy. ,” . Acquisti, Taylor, and Wagman, . Journal of Economic Literature.