PPT-Formal Abstractions for Attested Execution Secure Processor

Eurocrypt May 1 st 2017 Rafael Pass Elaine Shi Florian Tramèr Trusted hardware Different communities different world views Crypto Architecture Systems amp Security Minimal trusted . Vyas Sekar, Petros Maniatis. ISTC for Secure Computing . . 1. Amit. . Vasudevan. , Chen . Chen. , Adrian . Perrig. . CyLab. , Carnegie Mellon University. . Ubiquity of Outsourcing Computation. MySecureMeeting™ brings my client to me in one click of my computer for communication in a secured platform. I’m face to face with my clients, anywhere, anytime removing the boundaries of location. Validating thru visual communication the important points of our meeting eliminates lost opportunities, saves time, and money. EHR Incentive Programs. HIT Policy Committee. July 8, 2014. . 2. 2014 Attestations thru July 1. 2823 Eligible Professionals attested for the 2014 Reporting Year. 443 are new participants. 972 attested to Stage 2. Watercolor Paint - Abstractions. Watercolor Paint – Non-Representational. Pastel Abstractions. 6/16/2010. Parallel Programming Abstractions. 1. Tasks . vs. Threads. Similar but not the same.. 6/16/2010. Parallel Programming Abstractions. 2. h/w processors. Operating System. T. hreads. Task Scheduler. CS. . 111. On-Line MS Program. Operating . Systems . Peter Reiher. . Introduction. Most useful abstractions an OS wants to offer can’t be directly realized by hardware. The hardware doesn’t do exactly what the abstraction requires. (for when semi-honest is only semi-good-enough). David Evans. University of Virginia. http://www.cs.virginia.edu/evans. http://www.MightBeEvil.com. DHOSA MURI Review. UVa. Falls Church. 8 December 2011. Data Analytics Update. January 27, 2015. Describe eligible . h. ospital attestation patterns. Define stage 2 eligible providers. Describe preliminary stage 2 attestation patterns. 2. Agenda. Attestation trends. Chapter 1 — Computer Abstractions and Technology — . 2. Classes of Computers. Personal computers. General purpose, variety of software. Subject to cost/performance tradeoff. Server computers. Network based. CSE 332 Data Abstractions: A Heterozygous Forest of AVL, Splay, and B Trees Kate Deibel Summer 2012 July 2, 2012 CSE 332 Data Abstractions, Summer 2012 1 From last time… Binary search trees can give us great performance due to providing a structured binary search. Lecture 19: Analysis of Fork-Join Parallel Programs. Dan Grossman. Spring 2010. Where are we. Done:. How to use . fork. , and . join. to write a parallel algorithm. Why using divide-and-conquer with lots of small tasks is best. Lecture 6: Dictionaries; Binary Search Trees. Dan Grossman. Spring 2010. Where we are. Studying the absolutely essential ADTs of computer science and classic data structures for implementing them. ADTs so far:. Lecture 9: B Trees. Dan Grossman. Spring 2010. Our goal. Problem: A dictionary with so much data most of it is on disk. Desire: A balanced tree (logarithmic height) that is even shallower than AVL trees so that we can minimize disk accesses and exploit disk-block size. Lecture 15: Introduction to Graphs. Dan Grossman. Spring 2010. Graphs. A graph is a formalism for representing relationships among items. Very general definition because very general concept. A . graph.