The Future of Systematic Information Protection
Bob Hutchinson
Sandia National Laboratory
Albuquerque, NM 87185-0165
+1 (505)844-4131
Monday March 14, 2005 - Keynote Address

Information plays a critical role in global economics as well as our security, safety, and quality of life. There is a growing disparity between the value of information and our capability to manage and protect it. Technical and policy research is needed to address this disparity. Fundamentally, we can not answer the following question, "how much security is enough?" We lack the capability to quantify the value of information, particularly information that has been processed and aggregated. We also face many difficulties when attempting to measure information security, characterize threats, understand vulnerabilities, or even formulate and sustain any specific security posture. As a result, we can not measure our risk and therefore can not manage it. Our efforts to address this problem can be divided into two categories, legal/policy and technical. Owners of physical assets, such as cash or gold, have the legal and technical means to augment fortification protections with armed guards and lethal force. From a legal perspective, protection of information is limited to fortification, in part because we lack sufficient attribution. From a technical perspective, we have built complex mountains of computer code on top of hardware architectures that will attempt to execute any arbitrary instructions. These systems cannot be effectively analyzed for vulnerabilities so as to ensure trustworthy and secure operation. Research is needed to address the systematic protection of information including information valuation, security metrics, strong attribution, trustworthy computing, sustainable security processes, and legal devices that will support comprehensive protection and risk management.

Speaker's Bio
Born: 12/06/1964
Education: BSEE University of New Mexico, 1986
MSEE Stanford University, 1988
MBA UNM Anderson School of Management, 2003

Professional experience:
1999-2005 Manager of Network Security Research Department, Sandia National Laboratories
1999-2005 Manager of Sandia's Cyber Defender Program in New Mexico
2000-2005 Adjunct Professor of Information Assurance, New Mexico Tech
1988-2000 Principal Member of Technical Staff, Sandia National Laboratories

Research and development experience:
Secure network design for military command and control systems
Information assurance for high consequence systems
High performance (10Gbps) network security research
Multi-level security research and development
Information security R&D for digital process control systems
Patents in the following technical areas:
Multi-domain security using standards-compliant commercial equipment
High-performance, agile security through programmable logic


Order Relations and Rigor in Computing
Ramon E. Moore, Ph.D.
40 Orchard Drive
Worthington, Ohio 43085

Wednesday March 16, 2005 - Keynote Address

People quit saying "computers don't make mistakes" after the Y2K scare that generated billions of dollars in hardware upgrades, and hence the " bubble". Computer arithmetic with finite-length bit-strings has its limitations and creates concerns. In computational mathematics using computers, it is a pity to abandon rigor just at the point we have reduced the problem to computer algorithms. In fact we need not do so. By using pairs of machine numbers as upper and lower bounds of unknown numbers of interest, and by rounding upper bounds up and lower bounds down, we can modify ordinary floating-point machine arithmetic to produce mathematically rigorous results. This is called "interval arithmetic with outward rounding", and it has been implemented and used for several decades. In particular it has been successfully used in non-trivial computer-aided proofs in mathematical analysis, such as the Kepler conjecture (a problem that was outstanding for more than 300 years) and many others. Practical applications also abound in chemical engineering, structural engineering, economics, aircraft control circuitry design, beam physics, global optimization, differential equations, etc. Rigor in computing depends on the integrity of order relations. Commonly used floating-point hardware can lose that integrity. A few examples are presented and it is shown how we can remedy the situation and regain rigor in computing by using outwardly rounded interval arithmetic.

Speaker's Bio
Born: 12/27/29 Sacramento, California
Education: AB, Physics, University of California-Berkeley, 1950
PhD, Mathematics, Stanford University, 1963

Professional experience:
1986-2000 Professor, Computer and Information Science, Ohio State Univ.
1982-86 Professor, Mathematics, Univ.of Texas-Arlington
1968-81 Professor, Computer Sciences, Univ. of Wisconsin-Madison
1965-68 Associate Professor, Univ. of Wisconsin-Madison
1956-64 Lockheed Palo Alto Research Laboratories
1953-56 Univ. of California Radiation Laboratory-Livermore
1950-53 Computing Center, Aberdeen Proving Ground, Maryland

Visiting Professorships:
1980 Freiburg, Germany
1975 Karlsruhe, Germany
1974 Oxford, England
1967 Stockholm, Sweden
1965 Mathematics Research Center, Univ. of Wisconsin-Madison

2004 Michigan State University
2000-2002 Sun Microsystems
1985-86 Lockheed MSC
1978-79 The World Bank

Society for Industrial and Applied Mathematics

Alexander von Humboldt Foundation, US Senior Scientist Award, 1975, 1980

Books authored:
Computational Functional Analysis, Ellis Horwood and John Wiley, 1985
Methods and Applications of Interval Analysis, S. I. A. M., 1979
Mathematical Elements of Scientific Computing, Holt, Rinehart&Winston, 1975
Computation and Theory in Ordinary Differential Equations (with J. W. Daniel), W. Freeman & Co., 1970
Interval Analysis, Prentice-Hall, 1966

Books edited:
Reliability in Computing, Academic Press, 1988

Selected Refereed Papers:

Interval analysis and fuzzy set theory (with Weldon Lodwick), Fuzzy Sets and Systems, 135 (2003), 5-9

Sparse systems in fixed point form, Reliable Computing, Vol. 8, No. 4 (2002), 249-265

Interval analysis:systems of nonlinear equations; Interval analysis: differential equations
in Encyclopedia of Optimization (Eds: C.A.Floudas&P.M.Pardalos) Kluwer Academic (2001), 8-11, 34-40

Numerical solutions of differential equations to prescribed accuracy, Computers and Mathematics with Applications, 28, 10/12 (1994), 253-261

On the resolution of close minima, Computers and Mathematics with Applications, 25, 10/11 (1993), 57-58

Parameter sets for bounded-error data, Mathematics and Computers in Simulation, 34 (1992), 113-119

Rigorous methods for parallel global optimization (with E. Hansen and A. Leclerc), in Recent Advances in Global Optimization (Eds:C.A.Floudas&P.M.Pardalos), Princeton Univ. Press (1992), 321-342

Interval tools for computer-aided proofs in analysis, in Computer Aided Proofs in Analysis, (Eds: K.Meyer&D.Schmidt), Springer (1991), 211-216

Simple simultaneous super-and subfunctions, Journal of Integral Equations,8,1985, 165-174

Set-valued extensions of integral inequalities, J. Integral Equations, 5, 1983, 187-198

A generalization of the method of upper and lower solutions for integral equations, Nonlinear Analysis TMA, 6, 8, 1982, 829-831

On computing the range of values (with N.S.Asaithambi&Shen Zuhe), Computing 28, 1982,

New results on nonlinear systems, in Interval Mathematics 1980 (ed. K. Nickel), Academic Press (1980), 165-180

Interval methods for nonlinear systems, Computing, Suppl. 2, 1980, 113-120

A simple test for accuracy of approx. solutions to nonlinear systems (with J.B.Kioustelidis),
SIAM J. Numer. Anal., 17, 4, 1980, 521-529

A computational test for convergence of iterative methods for nonlinear systems, SIAM J. Numer. Anal., 15, 1978, 1194-1196

Bounding sets in function spaces with application to nonlinear operator equations, SIAM Review, 20, 1978, 492-512

Safe starting regions for iterative methods (with S. T. Jones), SIAM J. Numer. Anal., 14, 6, 1977, 1051-1065

A test for existence, SIAM J. Numer. Anal., 14, 4, 1977, 611-615

Two-sided approximations to solutions of nonlinear operator equations--a comparison of methods from classical analysis, functional analysis and interval analysis, in Interval Mathematics (Ed. K. Nickel), Lecture Notes in Computer Science, 29, Springer (1975), 31-47

On the stability of linear recurrence relations with arbitrary time lags, J. Computer&System Sciences, 4, 4, 1970, 377-383

Functional analysis for computers, In Funktional-analytische Methoden der Numerische Mathematik, Birkhauser (1969), 113-126

Practical aspects of interval computation, Aplikace Mathematiky, Svacek 13, Prague, 1968, 52-92

Inviscid flow in an accelerating cylindrical container (with L.M. Perko), J. Fluid Mechanics,
22, part 2, 1965, 305-320

Automatic coordinate transformations . . ., in Error in Digital Computation, Vol II, (Ed. L.B.Rall), Wiley (1965), 103-140

The automatic analysis and control of eror in digital computation based on the use of interval numbers, in Error in Digital Computation, Vol I, (Ed. L.B.Rall), Wiley (1965)

Interval arithmetic and automatic error analysis in digital computing, PhD dissertation,Stanford University (1962), published as Applied Mathematics and Statistics Laboratories Technical Report No. 25.