Continuous improvement of script-driven verifiable random functions for reducing computing power in blockchain consensus protocols

2021 ◽  
Author(s):  
Guanglai Guo ◽  
Yan Zhu ◽  
E Chen ◽  
Guizhen Zhu ◽  
Di Ma ◽  
...  
Keyword(s):  
Continuous Improvement ◽  
Computing Power ◽  
Random Functions ◽  
Verifiable Random Functions

scholarly journals A Novel Construction of Constrained Verifiable Random Functions

2019 ◽  
Vol 2019 ◽  
pp. 1-15
Author(s):  
Muhua Liu ◽  
Ping Zhang ◽  
Qingtao Wu
Keyword(s):  
Random Function ◽  
Secret Key ◽  
Bilinear Maps ◽  
Random Functions ◽  
Compute Function ◽  
Multilinear Maps ◽  
Verifiable Random Functions ◽  
Selective Security

Constrained verifiable random functions (VRFs) were introduced by Fuchsbauer. In a constrained VRF, one can drive a constrained key skS from the master secret key sk, where S is a subset of the domain. Using the constrained key skS, one can compute function values at points which are not in the set S. The security of constrained VRFs requires that the VRFs’ output should be indistinguishable from a random value in the range. They showed how to construct constrained VRFs for the bit-fixing class and the circuit constrained class based on multilinear maps. Their construction can only achieve selective security where an attacker must declare which point he will attack at the beginning of experiment. In this work, we propose a novel construction for constrained verifiable random function from bilinear maps and prove that it satisfies a new security definition which is stronger than the selective security. We call it semiadaptive security where the attacker is allowed to make the evaluation queries before it outputs the challenge point. It can immediately get that if a scheme satisfied semiadaptive security, and it must satisfy selective security.

scholarly journals Statically Aggregate Verifiable Random Functions and Application to E-Lottery

Cryptography ◽  
2020 ◽  
Vol 4 (4) ◽  
pp. 37
Author(s):  
Bei Liang ◽  
Gustavo Banegas ◽  
Aikaterini Mitrokotsa
Keyword(s):  
Random Function ◽  
Random Functions ◽  
Large Sets ◽  
Diffie Hellman ◽  
Winning Number ◽  
Verifiable Random Functions

Cohen, Goldwasser, and Vaikuntanathan (TCC’15) introduced the concept of aggregate pseudo-random functions (PRFs), which allow efficiently computing the aggregate of PRF values over exponential-sized sets. In this paper, we explore the aggregation augmentation on verifiable random function (VRFs), introduced by Micali, Rabin and Vadhan (FOCS’99), as well as its application to e-lottery schemes. We introduce the notion of static aggregate verifiable random functions (Agg-VRFs), which perform aggregation for VRFs in a static setting. Our contributions can be summarized as follows: (1) we define static aggregate VRFs, which allow the efficient aggregation of VRF values and the corresponding proofs over super-polynomially large sets; (2) we present a static Agg-VRF construction over bit-fixing sets with respect to product aggregation based on the q-decisional Diffie–Hellman exponent assumption; (3) we test the performance of our static Agg-VRFs instantiation in comparison to a standard (non-aggregate) VRF in terms of costing time for the aggregation and verification processes, which shows that Agg-VRFs lower considerably the timing of verification of big sets; and (4) by employing Agg-VRFs, we propose an improved e-lottery scheme based on the framework of Chow et al.’s VRF-based e-lottery proposal (ICCSA’05). We evaluate the performance of Chow et al.’s e-lottery scheme and our improved scheme, and the latter shows a significant improvement in the efficiency of generating the winning number and the player verification.

Exploiting the Capabilities of Experiment and Numerical Methods

2006 ◽  
Author(s):  
Steven J. Herring
Keyword(s):  
Numerical Methods ◽  
Continuous Improvement ◽  
Physical Models ◽  
Test Cycle ◽  
Complex Flows ◽  
Time To Market ◽  
Computing Power ◽  
Commercial Drivers ◽  
User Friendly ◽  
Accuracy And Repeatability

The last 20 years has seen the development of reliable, user-friendly, RANS CFD codes which can model the steady state features of complex flows. This coupled with the diminishing cost of computing power has made the solution of large problems economical. As result of this there has been a significant reduction in the amount of testing activity undertaken. Nevertheless, high quality experiments remain essential, and the real need is to effectively exploit the strengths of the two approaches. Whilst improvements in theoretical aerodynamic methods may be leading to a decline in test activity as a whole, paradoxically, it also means that when tests are carried out there is a need for the data to be of an ever increasing quality and quantity. There are two key commercial drivers acting on test activities which are: to achieve reductions in overall test costs and to reduce the test cycle time as a part of the broader goal of reducing time to market. The paper discusses the strengths and weaknesses of experimental and numerical methods, with reference to the limitations on resolution and intrusive effect of instrumentation, and the limitations of the physical models within numerical methods. From this conclusions are drawn regarding how the two approaches complement each other. The levels of accuracy and repeatability now required in turbomachinery testing are discussed with reference to work carried out at Cranfield University. The need for a continuous improvement in both capabilities and cost effectiveness of test facilities is identified.

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