46718511
Capability-Based Financial Instruments
Every novel cooperative arrangement of mutually suspicious parties interacting electronically -- every smart contract -- effectively requires a new cryptographic protocol. However, if every new contract requires new cryptographic protocol design, our dreams of cryptographically enabled electronic commerce would be unreachable. Cryptographic protocol design is too hard and expensive, given our unlimited need for new contracts.Just as the digital logic gate abstraction allows digital circuit designers to create large analog circuits without doing analog circuit design, we present cryptographic capabilities as an abstraction allowing a similar economy of engineering effort in creating smart contracts. We explain the E system, which embodies these principles, and show a covered-call-option as a smart contract written in a simple security formalism independent of cryptography, but automatically implemented as a cryptographic protocol coordinating five mutually suspicious parties.
16608960
Objects in Concurrent Logic Programming Languages
Concurrent Prolog supports object-oriented programming with a clean semantics and additional programming constructs such as incomplete messages, unification, direct broadcasting, and concurrency synchronization [Shapiro 1983a]. While it provides excellent computational support, we claim it does not provide good notation for expressing the abstractions of object-oriented programming. We describe a preprocessor that remedies this problem. The resulting language, Vulcan, is then used as a behicle for exploring new variants of object-oriented programming which become possible in this framework.
40582600
Concurrency Among Strangers
Programmers write programs, expressing plans for machines to execute. When composed so that they may cooperate, plans may instead interfere with each other in unanticipated ways. Plan coordination is the art of simultaneously enabling plans to cooperate, while avoiding hazards of destructive plan interference. For sequential computation within a single machine, object programming supports plan coordination well. For concurrent computation, this paper shows how hard it is to use locking to prevent plans from interfering without also destroying their ability to cooperate.
1871640
Exploring the Energy-Latency Trade-Off for Broadcasts in Energy-Saving Sensor Networks
Networking protocols for multi-hop wireless sensor networks (WSNs) are required to simultaneously minimize resource usage as well as optimize performance metrics such as latency and reliability. This paper explores the energy-latency-reliability trade-off for broadcast in multi-hop WSNs, by presenting a new protocol called PBBF (probability-based broadcast forwarding). PBBF works at the MAC layer and can be integrated into any sleep scheduling protocol. For a given application-defined level of reliability for broadcasts, the energy required and latency obtained are found to be inversely related to each other. Our analysis and simulation study quantify this relationship at the reliability boundary, as well as performance numbers to be expected from a deployment. PBBF essentially offers a WSN application designer considerable flexibility in choice of desired operation points
15180139
Bayesian Segmentation via Asymptotic Partition Functions
Asymptotic approximations to the partition function of Gaussian random fields are derived. Textures are characterized via Gaussian random fields induced by stochastic difference equations determined by finitely supported, stationary, linear difference operators, adjusted to be nonstationary at the boundaries. It is shown that as the scale of the underlying shape increases, the log-normalizer converges to the integral of the log-spectrum of the operator inducing the random field. Fitting the covariance of the fields amounts to fitting the parameters of the spectrum of the differential operator-induced random field model. Matrix analysis techniques are proposed for handling textures with variable orientation. Examples of texture parameters estimated from training data via asymptotic maximum-likelihood are shown. Isotropic models involving powers of the Laplacian and directional models involving partial derivative mixtures are explored. Parameters are estimated for mitochondria and actin-myocin complexes in electron micrographs and clutter in forward-looking infrared images. Deformable template models are used to infer the shape of mitochondria in electron micrographs, with the asymptotic approximation allowing easy recomputation of the partition function as inference proceeds.
35339559
Two new families of large compound graphs
A question of special interest in graph theory is the design of large graphs. Specifically, we want to find constructions of graphs with order as large as possible for a given degree and diameter D . Two generalizations of two large compound graphs are proposed in this article. Three particular cases of these families of graphs presented here allow us to improve the order for the entries (15, 7), (13, 10), and (15, 10) in the table of the largest known ( , D)-graphs. © 2006 Wiley Periodicals, Inc. NETWORKS, Vol. 47(3), 140–146 2006
12989752
Asymptotic performance analysis of Bayesian target recognition
This article investigates the asymptotic performance of Bayesian target recognition algorithms using deformable-template representations. Rigid computer-aided design (CAD) models represent the underlying targets; low-dimensional matrix Lie-groups (rotation and translation) extend them to particular instances. Remote sensors observing the targets are modeled as projective transformations, converting three-dimensional scenes into random images. Bayesian target recognition corresponds to hypothesis selection in the presence of nuisance parameters; its performance is quantified as the Bayes' error. Analytical expressions for this error probability in small noise situations are derived, yielding asymptotic error rates for exponential error probability decay.
7955941
Leveraging Channel Diversity for Key Establishment in Wireless Sensor Networks
As the use of sensor networks increases, security in this domain becomes a very real concern. One fundamental aspect of providing confidentiality and authentication is key distribution. While public-key encryption has provided these properties historically, sensors are resource constrained and benefit from symmetric key approaches. In this work, we propose a novel protocol for symmetric key distribution that uses the multiple channels available on sensor hardware. This channel diversity, along with spatial diversity of device locations, allows neighboring sensors to establish secure link keys from plaintext keys that are broadcast by sensors in their neighborhood. In particular, we show that using even one extra channel during the initialization procedure significantly improves the security of key establishment. Via analysis and simulation, we show that our protocol performs well in terms of network connectivity and resilience to colluding malicious devices, when compared to previous work. We show that our protocol can achieve over 90% connectivity among neighboring sensors with link keys that are uncompromised even when 80% of the devices in the network are malicious and collude. Finally, we present a thorough discussion of the comparative advantages and disadvantages of our approach compared to previous techniques.