A Modular Treatment of Blind Signatures from Identification Schemes

2019 ◽  
pp. 345-375 ◽  
Author(s):  
Eduard Hauck ◽  
Eike Kiltz ◽  
Julian Loss
Keyword(s):  
Identification Schemes ◽  
Blind Signatures ◽  
Modular Treatment

An Electronic Cash System Based on Group Blind Signatures

Informatica ◽  
2006 ◽  
Vol 17 (4) ◽  
pp. 551-564 ◽  
Author(s):  
Constantin Popescu
Keyword(s):  
Electronic Cash ◽  
Blind Signatures

Publicly auditable conditional blind signatures

2021 ◽  
Vol 29 (2) ◽  
pp. 229-271
Author(s):  
Panagiotis Grontas ◽  
Aris Pagourtzis ◽  
Alexandros Zacharakis ◽  
Bingsheng Zhang
Keyword(s):  
Proof Of Concept ◽  
Equivalence Test ◽  
Zero Knowledge ◽  
Private Key ◽  
Blind Signatures ◽  
Cryptographic Primitive ◽  
Security Properties ◽  
Designated Verifier

This work formalizes Publicly Auditable Conditional Blind Signatures (PACBS), a new cryptographic primitive that allows the verifiable issuance of blind signatures, the validity of which is contingent upon a predicate and decided by a designated verifier. In particular, when a user requests the signing of a message, blinded to protect her privacy, the signer embeds data in the signature that makes it valid if and only if a condition holds. A verifier, identified by a private key, can check the signature and learn the value of the predicate. Auditability mechanisms in the form of non-interactive zero-knowledge proofs are provided, so that a cheating signer cannot issue arbitrary signatures and a cheating verifier cannot ignore the embedded condition. The security properties of this new primitive are defined using cryptographic games. A proof-of-concept construction, based on the Okamoto–Schnorr blind signatures infused with a plaintext equivalence test is presented and its security is analyzed.

The Individualization of the Little Talks Intervention: Implications for Modular Treatment Designs

2021 ◽  
pp. 105381512110249
Author(s):  
Diamond S. Carr ◽  
Patricia H. Manz
Keyword(s):  
Parent Involvement ◽  
Head Start ◽  
Home Visiting ◽  
Frequent Change ◽  
Home Visitors ◽  
Intervention Content ◽  
Modular Treatment ◽  
Book Sharing ◽  
Treatment Designs

Modular treatment designs enable interventionists to adapt intervention content to individual clients, a process referred to as individualization. Little is known about individualization processes and its effects on outcomes in early childhood services. This exploratory study investigated individualization processes undertaken by Early Head Start home visitors as they provided Little Talks, a modularized book-sharing intervention for families. It also examined the effect of individualization on parent involvement in early learning activities. Two indicators of individualization were calculated in this study: (a) the proportion of change in the Little Talks’ lessons sequence and (b) the pace of delivery. Findings showed that most home visitors individualized Little Talks, with the most frequent change being the repetition of lessons. Exploratory regression analysis showed an inverse relationship between home visitors’ individualization behavior and parent involvement, highlighting the need to examine the quality of individualization. Implications for advancing the implementation and study of individualization processes in home visiting are discussed.

scholarly journals Choosing between identification schemes in noisy-news models

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Joshua C. C. Chan ◽  
Eric Eisenstat ◽  
Gary Koop
Keyword(s):  
Bayesian Methods ◽  
Moving Average ◽  
Autoregressive Moving Average ◽  
Structural Shocks ◽  
Vector Autoregressive ◽  
Identification Scheme ◽  
Identification Schemes ◽  
The One ◽  
Small Models ◽  
Structural Vector

AbstractThis paper is about identifying structural shocks in noisy-news models using structural vector autoregressive moving average (SVARMA) models. We develop a new identification scheme and efficient Bayesian methods for estimating the resulting SVARMA. We discuss how our identification scheme differs from the one which is used in existing theoretical and empirical models. Our main contributions lie in the development of methods for choosing between identification schemes. We estimate specifications with up to 20 variables using US macroeconomic data. We find that our identification scheme is preferred by the data, particularly as the size of the system is increased and that noise shocks generally play a negligible role. However, small models may overstate the importance of noise shocks.

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