16701916
Probabilistic Bisimulation and Equivalence for Security Analysis of Network Protocols
Using a probabilistic polynomial-time process calculus designed for specifying security properties as observational equivalences, we develop a form of bisimulation that justifies an equational proof system. This proof system is sufficiently powerful to derive the semantic security of El Gamal encryption from the Decision Diffie-Hellman (DDH) assumption. The proof system can also derive the converse: if El Gamal is secure, then DDH holds. While these are not new cryptographic results, these example proofs show the power of probabilistic bisimulation and equational reasoning for protocol security.
16397953
Parametricity and Variants of Girard's J Operator
Abstract The Girard–Reynolds polymorphic λ -calculus is generally regarded as a calculus of parametric polymorphism in which all well-formed terms are strongly normalizing with respect to β -reductions. Girard demonstrated that the addition of a simple “non-parametric” operation, J , to the calculus allows the definition of a non-normalizing term. Since the type of J is not inhabited by any closed term, one might suspect that this may play a role in defining a non-normalizing term using it. We demonstrate that this is not the case by giving a simple variant, J′ , of J whose type is otherwise inhabited and which causes normalization to fail. It appears that impredictivity is essential to the argument; predictive variants of the polymorphic λ -calculus admit non-parametric operations without sacrificing normalization.
18708753
Unification and ML-Type Reconstruction
We study the complexity of type reconstruction for a core fragment of ML with lambda abstraction, function application, and the polymorphic let declaration. We derive exponential upper and lower bounds on recognizing the typable core ML expressions. Our primary technical tool is uniication of succinctly represented type expressions. After observing that core ML expressions, of size n, can be typed in DTIME(2 n), we exhibit two diierent families of programs whose principal types grow exponentially. We show how to exploit the expressiveness of the let-polymorphism in these constructions to derive lower bounds on deciding typability: one leads naturally to NP-hardness and the other to DTIME(2 n k)-hardness for each integer k 1. Our generic simulation of any exponential time Turing Machine by ML type reconstruction may be viewed as a nonstandard way of computing with types. Our worst-case lower bounds stand in contrast to practical experience, which suggests that commonly used algorithms for type reconstruction do not slow compilation substantially.
9031501
Design of a role-based trust-management framework
We introduce the RT framework, a family of role-based trust management languages for representing policies and credentials in distributed authorization. RT combines the strengths of role-based access control and trust-management systems and is especially suitable for attribute-based access control. Using a few simple credential forms, RT provides localized authority over roles, delegation in role definition, linked roles, and parameterized roles. RT also introduces manifold roles, which can be used to express threshold and separation-of-duty policies, and delegation of role activations. We formally define the semantics of credentials in the RT framework by presenting a translation from credentials to Datalog rules. This translation also shows that this semantics is algorithmically tractable.
3062362
Managing Digital Rights using Linear Logic
Digital music players protect songs by enforcing licenses that convey specific rights for individual songs or groups of songs. For licenses specified in industry, we show that deciding whether a license authorizes a sequence of actions is NP-complete, with a restricted version of the problem solvable efficiently using a reduction to maximum network flow. The authorization algorithm used in industry is online, deciding which rights to exercise as actions occur, but we show that all online algorithms are necessarily non-monotonic: each allows actions under one license that it does not allow under a more flexible license. In one approach to achieving monotonicity, we exhibit the unique maximal set of licenses on which there exists a monotonic online algorithm. This set of well-behaved licenses induces an approximation algorithm by replacing each license with a well-behaved license. In a second approach, we consider allowing the player to revise its past decisions about which rights to exercise while still ensuring compliance with the license. We propose an efficient algorithm based on linear logic, with linear negation used to revise past decisions. We prove our algorithm monotonic, live, and sound with respect to the semantics of licenses
215952437
Beyond proof-of-compliance: security analysis in trust management
Trust management is a form of distributed access control that allows one principal to delegate some access decisions to other principals. While the use of delegation greatly enhances flexibility an...
2908872
Automatic generation of triangular irregular networks using greedy cuts
Proposes a new approach to the automatic generation of triangular irregular networks (TINs) from dense terrain models. We have developed and implemented an algorithm based on the greedy principle used to compute minimum-link paths in polygons. Our algorithm works by taking greedy cuts ("bites") out of a simple closed polygon that bounds the yet-to-be triangulated region. The algorithm starts with a large polygon, bounding the whole extent of the terrain to be triangulated, and works its way inward, performing at each step one of three basic operations: ear cutting, greedy biting, and edge splitting. We give experimental evidence that our method is competitive with current algorithms and has the potential to be faster and to generate many fewer triangles. Also, it is able to keep the structural terrain fidelity at almost no extra cost in running time and it requires very little memory beyond that for the input height array.
14245718
Fast and effective stripification of polygonal surface models
A fundamental algorithmic problem in computer graphics is t hat of computing a succinct encoding of a triangulation of a polygo nal surface model in order to be able to transmit and render it efficie ntly. The goal is to take a given polygonal surface model, whose fac ts are given by (possibly multiply-connected) polygons, tria ngulate its facets, and then decompose the triangulation into a small nu mber of “tristrips,” each of which has its connectivity stored im plicitly in the ordering of the data points. We develop methods that ar e effective in solving the stripification problem, both in the ory (provably good encodings) and in practice. Our methods are based o n carefully constructed search trees in the dual graph, follo wed by algorithms to decompose dual trees into tristrips. One decomp osition algorithm is provably optimal (based on dynamic programmin g), allowing us a sound basis of comparison among our other (heur istic) algorithms. We demonstrate the speed and effectivenes s of our algorithms through a battery of experiments. In comparison with the recently released STRIPE system for stripification, we find that our stripifier,FTSG, produces comparable or better quality encodings, while requiring significantly less computing time on a large variety of datasets. Further, FTSG is carefully engineered and implemented to be robust, even in the face of highly degenerate and corrupted real-world data. CR Categories: I.3.3 [Computer Graphics]: Picture/Image Generation—displaying algorithms; I.3.5 [Computer Graph ics]: Computational Geometry and Object Modeling—Geometric alg orithm, languages, and systems.
495062
The Lazy Bureaucrat scheduling problem
We introduce a new class of scheduling problems in which the optimization is performed by the worker (single "machine") who performs the tasks. A typical worker's objective is to minimize the amount of work he does (he is "lazy"), or more generally, to schedule as inefficiently (in some sense) as possible. The worker is subject to the constraint that he must be busy when there is work that he can do; we make this notion precise both in the preemptive and nonpreemptive settings. The resulting class of "perverse" scheduling preblems, which we denote "Lazy Bureaucrat Problems," gives rise to a rich set of new questions that explore the distinction between maximization and minimization in computing optimal schedules.
207159283
Minimum-cost coverage of point sets by disks
We consider a class of geometric facility location problems in which the goal is to determine a set <i>X</i> of disks given by their centers <i>(t<sub>j</sub>)</i> and radii <i>(r<sub>j</sub>)</i> that cover a given set of demand points <i>Y∈R</i><sup>2</sup> at the smallest possible cost. We consider cost functions of the form Ε<i><sub>j</sub>f(r<sub>j</sub>)</i>, where <i>f(r)=r</i><sup>α</sup> is the cost of transmission to radius <i>r</i>. Special cases arise for α=1 (sum of radii) and α=2 (total area); power consumption models in wireless network design often use an exponent α>2. Different scenarios arise according to possible restrictions on the transmission centers <i>t<sub>j</sub></i>, which may be constrained to belong to a given discrete set or to lie on a line, etc.We obtain several new results, including (a) exact and approximation algorithms for selecting transmission points <i>t<sub>j</sub></i> on a given line in order to cover demand points <i>Y∈R</i><sup>2</sup>; (b) approximation algorithms (and an algebraic intractability result) for selecting an optimal line on which to place transmission points to cover <i>Y</i>; (c) a proof of NP-hardness for a discrete set of transmission points in <i>R<sup>2</sup></i> and any fixed α>1; and (d) a polynomial-time approximation scheme for the problem of computing a <i>minimum cost covering tour</i> (MCCT), in which the total cost is a linear combination of the transmission cost for the set of disks and the length of a tour/path that connects the centers of the disks.
10207039
A Constant-Factor Approximation Algorithm for the Geometric k-MST Problem in the Plane
We show that any rectilinear polygonal subdivision in the plane can be converted into a "guillotine" subdivision whose length is at most twice that of the original subdivision. "Guillotine" subdivisions have a simple recursive structure that allows one to search for "optimal" such subdivisions in polynomial time, using dynamic programming. In particular, a consequence of our main theorem is a very simple proof that the k-MST problem in the plane has a constant-factor polynomial-time approximation algorithm: we obtain a factor of 2 (resp., 3) for the L1 metric, and a factor of $2\sqrt{2}$ (resp., 3.266) for the L2 (Euclidean) metric in the case in which Steiner points are allowed (resp., not allowed).