Knowledge Flow Analysis for Security Protocols

Knowledge flow analysis offers a simple and flexible way to find flaws in security protocols. A protocol is described by a collection of rules constraining the propagation of knowledge amongst principals. Because this characterization corresponds closely to informal descriptions of protocols, it allows a succinct and natural formalization; because it abstracts away message ordering, and handles communications between principals and applications of cryptographic primitives uniformly, it is readily represented in a standard logic. A generic framework in the Alloy modelling language is presented, and instantiated for two standard protocols, and a new key management scheme.Comment: 20 page

Physical random functions

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2003.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 87-89).In general, secure protocols assume that participants are able to maintain secret key information. In practice, this assumption is often incorrect as an increasing number of devices are vulnerable to physical attacks. Typical examples of vulnerable devices are smartcards and Automated Teller Machines. To address this issue, Physical Random Functions are introduced. These are Random Functions that are physically tied to a particular device. To show that Physical Random Functions solve the initial problem, it must be shown that they can be made, and that it is possible to use them to provide secret keys for higher level protocols. Experiments with Field Programmable Gate Arrays are used to evaluate the feasibility of Physical Random Functions in silicon.by Blaise L.P. Gassend.S.M

Learning biophysically-motivated parameters for alpha helix prediction

Background: Our goal is to develop a state-of-the-art protein secondary structure predictor, with an intuitive and biophysically-motivated energy model. We treat structure prediction as an optimization problem, using parameterizable cost functions representing biological “pseudo-energies. ” Machine learning methods are applied to estimate the values of the parameters to correctly predict known protein structures. Results: Focusing on the prediction of alpha helices in proteins, we show that a model with 302 parameters can achieve a Qα value of 77.6 % and an SOVα value of 73.4%. Such performance numbers are among the best for techniques that do not rely on external databases (such as multiple sequence alignments). Further, it is easier to extract biological significance from a model with so few parameters. Conclusions: The method presented shows promise for the prediction of protein secondary structure. Biophysically-motivated elementary free-energies can be learned using SVM techniques to construct an energy cost function whose predictive performance rivals state-of-the-art. This method is general and can be extended beyond the all-alpha case described here. 1 Backgroun

Fully microfabricated 2D electrospray array with applications to space propulsion

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 257-269).This thesis presents the design, fabrication and testing of a fully-integrated planar electrospray thruster array, which could lead to more efficient and precise thrusters for space propulsion applications. The same techniques could be used for making arrays to increase throughput in many other electrospray applications. Electrospray thrusters work by electrostatically extracting and accelerating ions or charged droplets from a liquid surface to produce thrust. Emission occurs from sharp emitter tips, which enhance the electric field and constrain the emission location. The electrospray process limits the thrust from a single tip, so that achieving millinewton thrust levels requires an array with tens of thousands of emitters. Silicon batch microfabrication has been used, as it is well suited for making large arrays of emitters. The thruster is made using Deep Reactive Ion Etching (DRIE) and wafer bonding techniques, in a six mask process, and comprises two components. The emitter die with up to 502 emitters in a 113 mm2 area, is formed using DRIE and SF6 etching, and is plasma treated to transport liquid to the tips in a porous black-silicon surface layer. The extractor die incorporates the extractor electrode, a Pyrex layer for insulation, and springs which are used to reversibly assemble the emitter die. This versatile assembly method, with 10 µm RMS alignment accuracy and 1.3 µm RMSD repeatability, allows the extractor die to be reused with multiple emitter dies, and potentially with different emitter concepts than the one presented. The thruster, weighing 5 g, was tested with the ionic liquids EMI-BF4 and EMIIm. Time of flight measurements show that the thruster operates in the ion emission regime most efficient for propulsion, with a specific impulse around 3000 s at a 1 kV extractor voltage. Emission starts as low as 500 V. Currents of 370 nA per emitter have been recorded at 1500 V, for an estimated thrust of 26 nN per emitter or 13 µN total, and a 275 mW power consumption. The thrust efficiency is estimated around 85%. In good operating conditions, the current intercepted on the extractor electrode is well below 1%, increasing to a few percent at the highest current levels. The beam divergence half width half maximum is between 10 and 15°.by Blaise Laurent Patrick Gassend.Ph.D

ABSTRACT Silicon Physical Random Functions

We describe the notion of a Physical Random Function (PUF). We argue that a complex integrated circuit can be viewed as a silicon PUF and describe a technique to identify and authenticate individual integrated circuits (ICs). We describe several possible circuit realizations of di erent PUFs. These circuits have been implemented in commodity Field Programmable Gate Arrays (FPGAs). We present experiments which indicate that reliable authentication of individual FPGAs can be performed even in the presence of signi cant environmental variations. We describe how secure smart cards can be built, and also brie y describe how PUFs can be applied to licensing and certi cation applications. Categories and Subject Descriptor