Theory Generation for Security Protocols

Frontiers in Research and Education in Computing: A View from the National Science Foundation Jeannette M. Wing Assistant Director Computer and Information Science and Engineering and Presidents Professor of Computer Science Carnegie Mellon University OOPSLA October 28, 2009 Orlando, FL ro c A t Cu s e ti i l

sibi ss n Computing: ein Frontiers in Research and Education S g n i eer n i g n e E Science Foundation A View from the National r a w oft

dS n a s age u g n La g n i mm a r g o Pr Jeannette M. Wing Assistant Director Computer and Information Science and Engineering

and Presidents Professor of Computer Science Carnegie Mellon University OOPSLA October 28, 2009 Orlando, FL NSF OOPSLA 4 Jeannette M. Wing OOPSLA 5 Jeannette M. Wing General Themes

Fundamental, long-term research High-risk, high-return, potentially transformative Inter- and multi-disciplinary Multi-perspective, collaborative Partnerships Academia ecosystem Industry Government Societal Grand Challenges OOPSLA 7 Jeannette M. Wing

CISE-specific NSF-wide Investments CDI: Cyber-Enabled Discovery and Innovation Computational Thinking for Science and Engineering Paradigm shift Not just computings metal tools (transistors and wires) but also our mental tools (abstractions and methods) Its about partnerships and transformative research. To innovate in/innovatively use computational thinking; and To advance more than one science/engineering discipline. Investments by all directorates and offices FY08: $48M, 1800 Letters of Intent, 1300 Preliminary Proposals, 200 Full Proposals, 36 Awards FY09: $63M+, 830 Prelimary Proposals, 283 Full Proposals, 53+ Awards OOPSLA 9

Jeannette M. Wing Range of Disciplines in CDI Awards OOPSLA

Aerospace engineering Astrophysics and cosmology Atmospheric sciences Biochemistry Biomaterials Biophysics Chemical engineering Civil engineering Communications science and engineering Computer science Cosmology

Ecosystems Genomics Geosciences 10 Linguistics Materials engineering Mathematics Mechanical engineering Molecular biology Nanocomputing Neuroscience Proteomics Robotics Social sciences Statistics Statistical physics Sustainability Jeannette M. Wing Range of Disciplines in CDI Awards

OOPSLA Linguistics Aerospace engineering Materials engineering Astrophysics and cosmology Mathematics Atmospheric sciences Mechanical engineering

Biochemistry Molecular biology Biomaterials CT includes Languages Nanocomputing Biophysics and Software Methods Chemical engineering Neuroscience Proteomics Civil engineering Robotics Communications science and engineering Social sciences Computer science Statistics Cosmology Statistical physics Ecosystems Sustainability Genomics

Geosciences advances via Computational Thinking 11 Jeannette M. Wing Science and Engineering Beyond Moores Law (not a special program) Three directorates: CISE, ENG, MPS All investing in core science, engineering, and technology Multi-core, many-core, massively parallel Programming models, languages, tools New, emerging substrates Nanocomputing Bio-inspired computing Quantum computing OOPSLA 12

Jeannette M. Wing CISE Core and Cross-Cutting Programs CCF CNS IIS Core Core Core Algorithmic Fns Communications & Information Fns Software & Hardware Fns

Computer Systems Network Systems Infrastructure Education & Workforce Human-Centered Information Integration & Informatics Robust Intelligence Cross-Cutting Cyber-Physical Systems Data-intensive Computing Network Science and Engineering Trustworthy Computing Plus many many other programs with other NSF directorates and other agencies OOPSLA 14 Jeannette M. Wing Expeditions Bold, creative, visionary, high-risk ideas

Whole >> part i i Solicitation is deliberately underconstrained Tell us what YOU want to do! Response to community Loss of ITR Large, DARPA changes, support for high-risk research, large experimental systems research, etc. Expect to fund 3 awards, each at $10M for 5 year OOPSLA 15 Jeannette M. Wing FY08-FY09 Awards What might be a good Expedition in Programming Languages and/or Software Engineering? FY08 Awards

Computational Sustainability Gomes, Cornell, Bowdoin College, the Conservation Fund, Howard University, Oregon State University and the Pacific Northwest National Laboratory Intractability Arora, Princeton, Rutgers, NYU, Inst for Adv. Studies Molecular Programming Winfrey, Cal Tech, UW Open Programmable Mobile Internet McKeown, Stanford FY09 Awards Robotic Bees Wood, Harvard

Modeling Tools for Disease and Complex Systems Clarke, CMU, NYU, Cornell, SUNY Stony Brook, University of Maryland Customized Computing Technology Cong, UCLA OOPSLA 16 Jeannette M. Wing Cross-Cutting Programs Drivers of Computing Society Science

OOPSLA Technology 19 Jeannette M. Wing Data Intensive Computing How Much Data? NOAA has ~1 PB climate data (2007) Wayback machine has ~2 PB (2006)

CERNs LHC will generate 15 PB a year (2008) HP is building WalMart a 4PB data warehouse (2007) AT&T handles 17.6PB of traffic over its backbone network a day (2009) Google processes 20 PB a day (2008) all words ever spoken by human beings ~ 5 EB Intl Data Corp predicts 1.8 ZB of digital data by 2011 640K ought to be enough for anybody. Slide source: Jimmy Lin, UMD OOPSLA 21 Jeannette M. Wing Convergence in Trends Drowning in data Data-driven approach in computer science research graphics, animation, language translation, search, , computational biology

Cheap storage Seagate Barracuda 1TB hard drive for $90 Growth in huge data centers Data is in the cloud not on your machine Easier access and programmability by anyone e.g., Amazon EC2, Google+IBM cluster, Yahoo! Hadoop OOPSLA 22 Jeannette M. Wing Data-Intensive Computing Sample Research Questions Science What are the fundamental capabilities and limitations of this paradigm? What new programming abstractions (including models, languages, algorithms) can accentuate these fundamental capabilities? What are meaningful metrics of performance and QoS? Technology How can we automatically manage the hardware and software of these

systems at scale? How can we provide security and privacy for simultaneous mutually untrusted users, for both processing and data? How can we reduce these systems power consumption? Society What (new) applications can best exploit this computing paradigm? OOPSLA 23 Jeannette M. Wing Data-Intensive Computing Infrastructure for CISE Community Google + IBM partnership announced in February 2008 Access to 1600+ nodes, software and services (Hadoop, Tivoli, etc.) Available to entire community Cluster Exploratory (CluE) seed program

April 23, 2008: Press release on CluE awards to 14 universities http://www.nsf.gov/news/news_summ.jsp?cntn_id=114686&org=NSF&from=news Oct 5-6, 2009: CluE PI meeting, Mountain View, CA https://wiki.umiacs.umd.edu/ccc/index.php/CLuE_PI_Meeting_2009 HP + Intel + Yahoo! + UIUC cluster announced in July 2008 1000+ nodes Bare machine, not just software (Hadoop) accessible Hosted at UIUC, available to entire community Beyond MapReduce! Other companies welcome! OOPSLA 24 Jeannette M. Wing Cyber-Physical Systems

Smart Cars A BMW is now actually a network of computers [R. Achatz, Seimens, Economist Oct 11, 2007] Credit: PaulStamatiou.com Cars drive themselves Lampsons Grand Challenge: Smart parking Reduce highway traffic deaths to zero. [Butler Lampson, Getting Computers to Understand, OOPSLA Microsoft, J. ACM 50, 1 (Jan. 2003), pp 70-72.] 26 Jeannette M. Wing Smart Fliers Credit: NASA/JPL smart helicopters

Credit: Boeing An airplane is a network of computers. CPS Luncheon 27 Credit: Harvard university smart insects Jeannette M. Wing Embedded Medical Devices Credit: Baxter International infusion pump pacemaker IBM Research

28 scanner Credit: Siemens AG Jeannette M. Wing Sensors Everywhere Credit: Arthur Sanderson at RPI Hudson River Valley Kindly donated by Stewart Johnston Sonoma Redwood Forest smart buildings Credit: MO Dept. of Transportation

OOPSLA smart 29 bridges Jeannette M. Wing Robots Everywhere Credit: Paro Robots U.S., Inc. At home: Paro, therapeutic robotic seal Credit: Carnegie Mellon University Credit: Honda At work: Two ASIMOs working together in coordination to deliver refreshments At home/clinics: Nursebot, robotic assistance for the elderly At home: iRobot Roomba vacuums

your house OOPSLA 30 Jeannette M. Wing Assistive Technologies for Everyone brain-computer interfaces of today Credit: Dobelle Institute memex of tomorrow Credit: Emotiv IBM Research 31 Jeannette M. Wing Credit: Paramount Pictures

What is Common to These Systems? They have a computational core that interacts with the physical world. Cyber-physical systems are engineered systems that require tight conjoining of and coordination between the computational (discrete) and the physical (continuous). Trends for the future Cyber-physical systems will be smarter and smarter. More and more intelligence will be in software. OOPSLA 32 Jeannette M. Wing Cyber-Physical Systems Sample Research Challenges Science Co-existence of Booleans and Reals Discrete systems in a continuous world Reasoning about uncertainty Human, Mother Nature, the Adversary

Technology Intelligent and safe digital systems that interact with the physical world Self-monitoring, real-time learning and adapting Society Systems need to be unintrusive, friendly, dependable, predictable, New Challenges for PL and SE communities: - Hybrid languages: discrete and continuous - Languages, logics, models with probabilistic state transitions: uncertainty - Software services systems that learn and adapt in real-time OOPSLA 33 Jeannette M. Wing A (Flower) Model for Expediting Progress Sectors Industry Govt (e.g., military) medical aero

finance Industry Govt Academia auto Fundamental Research Academia Govt (NSF, NSA, NIH, DoD, ) energy civil chemical OOPSLA 34

transportation materials Jeannette M. Wing Our Evolving Networks are Complex 1970 IBM Research 1980 36 1999 Jeannette M. Wing Our Evolving Networks are Complex

1970 IBM Research 1980 37 1999 Jeannette M. Wing Our Evolving Networks are Complex 1970 IBM Research 1980 38 1999

Jeannette M. Wing Network Science and Engineering Sample Research Challenges Science Understand the complexity of large-scale networks - Understand emergent behaviors, localglobal interactions, system failures and/or degradations - Develop models that accurately predict and control network behaviors Technology Develop new architectures, exploiting new substrates - Develop architectures for self-evolving, robust, manageable future networks - Develop design principles for seamless mobility support - Leverage optical and wireless substrates for reliability and performance - Understand the fundamental potential and limitations of technology

Society Enable new applications and new economies, while ensuring security and privacy - Design secure, survivable, persistent systems, especially when under attack - Understand technical, economic and legal design trade-offs, enable privacy protection - Explore AI-inspired and game-theoretic paradigms for resource and performance optimization OOPSLA 39 Network science and engineering researchers Distributed systems and substrate researchers Security, privacy,

economics, AI, social science researchers Jeannette M. Wing Network Science and Engineering Sample Research Challenges Science Understand the complexity of large-scale networks - Understand emergent behaviors, localglobal interactions, system failures and/or degradations - Develop models that accurately predict and control network behaviors Network science and engineering researchers Sample Challenges for PL and SE: - Models, logics, languages, tools, etc. for complex (emergent) behavior of

evolving networks Distributed Develop new architectures, Technology - Please see Pamela Zaves systems and exploiting newSoftware substratesEngineering for the Next Internet ICSE 2009 Keynote substrate - Develop architectures for self-evolving, robust, manageable future networks - Develop design principles for seamless mobility support - Leverage optical and wireless substrates for reliability and performance - Understand the fundamental potential and limitations of technology Society Enable new applications and new economies,

while ensuring security and privacy - Design secure, survivable, persistent systems, especially when under attack - Understand technical, economic and legal design trade-offs, enable privacy protection - Explore AI-inspired and game-theoretic paradigms for resource and performance optimization OOPSLA 40 researchers Security, privacy, economics, AI, social science researchers Jeannette M. Wing Trustworthy Computing Trustworthy = reliability, security, privacy, usability Deepen and broaden Cyber Trust Three emphases for FY09 Foundations of trustworthy Models, logics, languages, algorithms, metrics

E.g., Science of Security Privacy Usability OOPSLA too 41 Jeannette M. Wing New for FY10 Clickworkers Collaborative Filtering Collaborative Intelligence Collective Intelligence Computer Assisted Proof Crowdsourcing eSociety Genius in the Crowd

Human-Based Computation Participatory Journalism Pro-Am Collaboration Recommender Systems Reputation Systems Social Commerce Social Computing Social Technology Swarm Intelligence Wikinomics Wisdom of the Crowds DAC 43 Jeannette M. Wing l l a i c So

DAC l e t n I y n e lig 44 m o tC Clickworkers Collaborative Filtering Collaborative Intelligence

Collective Intelligence Computer Assisted Proof Crowdsourcing eSociety Genius in the Crowd Human-Based Computation Participatory Journalism Pro-Am Collaboration Recommender Systems Reputation Systems Social Commerce Social Computing Social Technology Swarm Intelligence Wikinomics Wisdom of the Crowds g n ti u p

Jeannette M. Wing Socially Intelligent Computing 19th C-20th C Computer ::= Human | Machine | Human + Machine | Network of Computer 20th C 20th-21st C now and future Sample Questions: - What is the collective intelligence of humans and machines working together? - When must we rely on the participation of humans for their reasoning ability (i.e., intelligence)? - What is computable by these kinds of computers? - Can we understand the capabilities of humans and computers working in harmony, solving problems neither can solve alone? - Can we design systems with intentional, rather than accidental behavior in mind? OOPSLA

45 Jeannette M. Wing Socially Intelligent Computing 19th C-20th C Computer ::= Human | Machine | Human + Machine | Network of Computer 20th C 20th-21st C now and future Sample Questions: New Challenges for PL and SE: and machines working together? - What is the collective

intelligence of humans - How program theseofcomputers? - When must we do relyyou on the participation humans for - Whatability languages? their reasoning (i.e., intelligence)? - What is computable - What software design and analysis methods? by these kinds of computers? - Can we understand the capabilities of humans and computers working in harmony, solving problems neither can solve alone?

- Can we design systems with intentional, rather than accidental behavior in mind? NSF (CISE+SBE) Social-Computational Systems (SoCS) (pronounced socks) Program OOPSLA 46 Jeannette M. Wing Others Joint with other directorates and offices

Activities with other agencies, e.g., DARPA, DHS, IARPA, NGA, NIH, NSA Partnerships with companies CISE + BIO + SBE + MPS: Computational Neuroscience (with NIH) CISE + EHR: Advanced Learning Technologies CISE + ENG: Cyber-Physical Systems, Multi-core (with SRC) CISE + MPS: FODAVA (with DHS), MCS CISE + OCI: DataNet OCI + CISE + ENG + GEO + MPS: PetaApps Creative IT (co-funding with other directorates) Google+IBM, HP+Intel+Yahoo!: Data-Intensive Computing SRC: Multi-core Research infrastructure: CRI, MRI Please see website www.cise.nsf.gov for full list.

OOPSLA 47 Jeannette M. Wing Research Ideas in the Works IT and Sustainability (Energy, Environment, Climate) IT as part of the problem and IT as part of the solution IT as a consumer of energy 2% (and growing) of world-wide energy use due to IT IT as a helper, especially for the other 98% Direct: reduce energy use, recycle, repurpose, Indirect: e-commerce, e-collaboration, telework -> reduction travel, Systemic: computational models of climate, species, -> inform science and inform policy Engages the entire CISE community

OOPSLA Modeling, simulation, algorithms Energy-aware computing Science of power management Sensors and sensor nets Intelligent decision-making Energy: A new measure of algorithmic complexity and system performance, along with time and space CISEs part of NSFs FY10 Climate Research Initiative 49 Jeannette M. Wing Computer Science and Economics Computer Science influencing Economics Economics influencing Computer Science - Automated mechanism design underlies electronic commerce,

e.g., ad placement, on-line auctions, kidney exchange - Internet marketplace requires revisiting Nash equilibria model - Use intractability for voting schemes to circumvent impossibility results Research Issues at the Interface of Computer Science and Economics Workshop - Ithaca, September 3-4, 2009, sponsored by CISE - Stellar line up of computer scientists and economists - http://www.cis.cornell.edu/conferences_workshops/CSECON_09/ OOPSLA 50 Jeannette M. Wing Computer Science and Biology Gene sequencing and bioinformatics are a given Trend now is looking at common principles between the two disciplines Complex systems

Uncertainty of environment Networked Real-time adaptation Fault-tolerant, resilient Information systems Programmed systems Synthetic biology First decade of CS+Bio was low-hanging fruit. Second decade will form deeper and closer connections. OOPSLA 51 Jeannette M. Wing Education Education Implications for K-12 Question and Challenge for the Computing Community:

What is an effective way of learning (teaching) computational thinking by (to) K-12? - What concepts can students (educators) best learn (teach) when? What is our analogy to numbers in K, algebra in 7, and calculus in 12? - We uniquely also should ask how best to integrate The Computer with teaching the concepts. Computer scientists are now working with educators and cognitive learning scientists to address these questions. OOPSLA 53 Jeannette M. Wing C.T. in Education: Community Efforts CRA-E Computing Community CSTA NSF

Rebooting College Board National Academies Computational Computational Thinking Thinking workshops K-12 BPC OOPSLA ACM-Ed CPATH AP

54 CSTB CT for Everyone Steering Committee Marcia Linn, Berkeley Al Aho, Columbia Brian Blake, Georgetown Bob Constable, Cornell Yasmin Kafai, U Penn Janet Kolodner, Georgia Tech Larry Snyder, U Washington Uri Wilensky, Northwestern Jeannette M. Wing Adding C to STEM STEM = Science, Technology, Engineering, and Mathematics Time is right. Society needs more STEM-capable students and teachers. Programming Languages and Software Engineering The Administration understands the importance of STEM. Sensibilities are critical to the C in STEM.

Hill Event to promote this vision Wed, May 29, 2009 12:00 - 1:30 PM B339 Rayburn House Office Building OOPSLA 55 Jeannette M. Wing Last Word: The Future of Computing is Bright! Drivers of Computing Society Science Technology J. Wing, Five Deep Questions in Computing, CACM January 2008 DAC

57 Jeannette M. Wing Drivers of Computing 7As Anytime Anywhere Affordable Access to Anything by Anyone Authorized. Society Science Technology What is computable? P = NP? (How) can we build complex

systems simply? What is intelligence? What is information? J. Wing, Five Deep Questions in Computing, CACM January 2008 DAC 58 Jeannette M. Wing Thank You! Credits Copyrighted material used under Fair Use. If you are the copyright holder and believe your material has been used unfairly, or if you have any suggestions, feedback, or support, please contact: [email protected] Except where otherwise indicated, permission is granted to copy, distribute, and/or modify all images in this document under the terms of the GNU Free Documentation license, Version 1.2 or

any later version published by the Free Software Foundation; with no Invariant Sections, no FrontCover Texts, and no Back-Cover Texts. A copy of the license is included in the section entitled GNU Free Documentation license (http://commons.wikimedia.org/wiki/Commons:GNU_Free_Documentation_License) The inclusion of a logo does not express or imply the endorsement by NSF of the entities' products, services or enterprises IBM Research 60 Jeannette M. Wing

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