scholarly journals From One to Many: Synced Hash-Based Signatures

2017 ◽  
Author(s):  
Santi J. Vives
Keyword(s):  
Real World ◽  
Building Block ◽  
Main Building ◽  
Unlimited Number ◽  
Real World Applications ◽  
Time Signature ◽  
The Cost

Hash-based signatures use a one-time signature (OTS) as its main building block, and transform it into a many-times scheme, to sign a larger number of signatures. In known constructions, the cost and the size of each signature increase as the number of needed signatures grows. In real-world applications, requiring a significant number of signatures, the signatures can get quite large. As a result, it is usually believed that post-quantum signatures based on hashes need more computation and much larger sizes than classical signatures. We introduce a construction to challenge that idea: we show that it is possible to construct a many-times signatures scheme that is more efficient than the OTS it is built from, rather than less.We study the generation of signatures in conjunction with a blockchain, like bitcoin. The proposed scheme permits an unlimited number of signatures. The size of each signatures is constant and the same as in the OTS. The verification cost starts the same as in the OTS and decreases with each new signature, becoming more efficient on average as the number of signatures grows.

scholarly journals Neural Representation and Learning of Hierarchical 2-additive Choquet Integrals

2020 ◽  
Author(s):  
Roman Bresson ◽  
Johanne Cohen ◽  
Eyke Hüllermeier ◽  
Christophe Labreuche ◽  
Michèle Sebag
Keyword(s):  
Real World ◽  
Choquet Integral ◽  
Marginal Utility ◽  
Decision Makers ◽  
Neural Representation ◽  
Automatic Identification ◽  
Neural Architecture ◽  
Real World Applications ◽  
Choquet Integrals ◽  
The Cost

Multi-Criteria Decision Making (MCDM) aims at modelling expert preferences and assisting decision makers in identifying options best accommodating expert criteria. An instance of MCDM model, the Choquet integral is widely used in real-world applications, due to its ability to capture interactions between criteria while retaining interpretability. Aimed at a better scalability and modularity, hierarchical Choquet integrals involve intermediate aggregations of the interacting criteria, at the cost of a more complex elicitation. The paper presents a machine learning-based approach for the automatic identification of hierarchical MCDM models, composed of 2-additive Choquet integral aggregators and of marginal utility functions on the raw features from data reflecting expert preferences. The proposed NEUR-HCI framework relies on a specific neural architecture, enforcing by design the Choquet model constraints and supporting its end-to-end training. The empirical validation of NEUR-HCI on real-world and artificial benchmarks demonstrates the merits of the approach compared to state-of-art baselines.

Rich-Media Interactive Simulations

2016 ◽  
pp. 261-283
Author(s):  
Suzanne Tsacoumis
Keyword(s):  
Real World ◽  
High Fidelity ◽  
Rich Media ◽  
Job Candidates ◽  
Real World Applications ◽  
Fidelity Measures ◽  
Time Required ◽  
The Cost ◽  
Interactive Simulations

High fidelity measures have proven to be powerful tools for measuring a broad range of competencies and their validity is well documented. However, their high-touch nature is often a deterrent to their use due to the cost and time required to develop and implement them. In addition, given the increased reliance on technology to screen and evaluate job candidates, organizations are continuing to search for more efficient ways to gather the information they need about one's capabilities. This chapter describes how innovative, interactive rich-media simulations that incorporate branching technology have been used in several real-world applications. The main focus is on describing the nature of these assessments and highlighting potential solutions to the unique measurement challenges associated with these types of assessments.

Private identity agreement for private set functionalities

2021 ◽  
pp. 1-29
Author(s):  
Ben Kreuter ◽  
Sarvar Patel ◽  
Ben Terner
Keyword(s):  
Real World ◽  
Research Community ◽  
Multiparty Computation ◽  
Privacy Requirements ◽  
Set Intersection ◽  
Real World Applications ◽  
Private Set Intersection ◽  
The Cost ◽  
Significant Attention ◽  
Private Identity

Private set intersection and related functionalities are among the most prominent real-world applications of secure multiparty computation. While such protocols have attracted significant attention from the research community, other functionalities are often required to support a PSI application in practice. For example, in order for two parties to run a PSI over the unique users contained in their databases, they might first invoke a support functionality to agree on the primary keys to represent their users. This paper studies a secure approach to agreeing on primary keys. We introduce and realize a functionality that computes a common set of identifiers based on incomplete information held by two parties, which we refer to as private identity agreement, and we prove the security of our protocol in the honest-but-curious model. We explain the subtleties in designing such a functionality that arise from privacy requirements when intending to compose securely with PSI protocols. We also argue that the cost of invoking this functionality can be amortized over a large number of PSI sessions, and that for applications that require many repeated PSI executions, this represents an improvement over a PSI protocol that directly uses incomplete or fuzzy matches.

scholarly journals On the Temperature of SAT Formulas

2021 ◽  
Author(s):  
Jesús Giráldez-Cru ◽  
Pedro Almagro-Blanco
Keyword(s):  
Artificial Intelligence ◽  
Formal Verification ◽  
Real World ◽  
Random Model ◽  
Community Structures ◽  
Sat Solving ◽  
Scale Free ◽  
Real World Applications ◽  
The Cost ◽  
Challenging Question

The remarkable advances in SAT solving achieved in the last years have allowed to use this technology in many real-world applications of Artificial Intelligence, such as planning, formal verification, and scheduling, among others. Interestingly, these industrial SAT problems are commonly believed to be easier than classical random SAT formulas, but estimating their actual hardness is still a very challenging question, which in some cases even requires to solve them. In this context, realistic pseudo-industrial random SAT generators have emerged with the aim of reproducing the main features shared by the majority of these application problems. The study of these models may help to better understand the success of those SAT solving techniques and possibly improve them. In this work, we present a model to estimate the temperature of real-world SAT instances. This temperature represents the degree of distortion into the expected structure of the formula, from highly structured benchmarks (more similar to real-world SAT instances) to the complete absence of structure (observed in the classical random SAT model). Our solution is based on the Popularity-Similarity (PS) random model for SAT, which has been recently presented to reproduce two crucial features of application SAT benchmarks: scale-free and community structures. The PS model is able to control the hardness of the generated formula by introducing some randomizations in the expected structure. Our solution is a first step towards a hardness oracle based on the temperature of SAT formulas, which may be able to estimate the cost of solving real-world SAT instances without solving them.

scholarly journals An Efficient Stereo Matching Network Using Sequential Feature Fusion

Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1045
Author(s):  
Jaecheol Jeong ◽  
Suyeon Jeon ◽  
Yong Seok Heo
Keyword(s):  
Building Block ◽  
Stereo Matching ◽  
Feature Fusion ◽  
Mobile Environments ◽  
Disparity Map ◽  
Matching Network ◽  
Main Building ◽  
Matching Networks ◽  
Disparity Range ◽  
The Cost

Recent stereo matching networks adopt 4D cost volumes and 3D convolutions for processing those volumes. Although these methods show good performance in terms of accuracy, they have an inherent disadvantage in that they require great deal of computing resources and memory. These requirements limit their applications for mobile environments, which are subject to inherent computing hardware constraints. Both accuracy and consumption of computing resources are important, and improving both at the same time is a non-trivial task. To deal with this problem, we propose a simple yet efficient network, called Sequential Feature Fusion Network (SFFNet) which sequentially generates and processes the cost volume using only 2D convolutions. The main building block of our network is a Sequential Feature Fusion (SFF) module which generates 3D cost volumes to cover a part of the disparity range by shifting and concatenating the target features, and processes the cost volume using 2D convolutions. A series of the SFF modules in our SFFNet are designed to gradually cover the full disparity range. Our method prevents heavy computations and allows for efficient generation of an accurate final disparity map. Various experiments show that our method has an advantage in terms of accuracy versus efficiency compared to other networks.

scholarly journals Electronic Phenomena of Transition Metal Oxides

Crystals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 256
Author(s):  
Christian Rodenbücher ◽  
Kristof Szot
Keyword(s):  
Solid State ◽  
Transition Metal ◽  
Metal Oxides ◽  
Real World ◽  
Transition Metal Oxides ◽  
Major Research ◽  
Research Fields ◽  
Real World Applications

Transition metal oxides with ABO3 or BO2 structures have become one of the major research fields in solid state science, as they exhibit an impressive variety of unusual and exotic phenomena with potential for their exploitation in real-world applications [...]

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