Integrating security evaluations into virtual commissioning

2020 ◽  
Author(s):  
Alexander Giehl ◽  
Norbert Wiedermann ◽  
Makan Tayebi Gholamzadeh ◽  
Claudia Eckert
Keyword(s):  
Virtual Commissioning ◽  
Security Evaluations

scholarly journals A Mathematical Problem for Security Analysis of Hash Functions and Pseudorandom Generators

2015 ◽  
Vol 26 (02) ◽  
pp. 169-194 ◽  
Author(s):  
Koji Nuida ◽  
Takuro Abe ◽  
Shizuo Kaji ◽  
Toshiaki Maeno ◽  
Yasuhide Numata
Keyword(s):  
Mathematical Problem ◽  
Security Analysis ◽  
Hash Functions ◽  
Future Research ◽  
Theoretical Frameworks ◽  
Pseudorandom Generators ◽  
Mathematical Problems ◽  
Security Evaluations ◽  
Security Property ◽  
Provably Secure

In this paper, we specify a class of mathematical problems, which we refer to as “Function Density Problems” (FDPs, in short), and point out novel connections of FDPs to the following two cryptographic topics; theoretical security evaluations of keyless hash functions (such as SHA-1), and constructions of provably secure pseudorandom generators (PRGs) with some enhanced security property introduced by Dubrov and Ishai (STOC 2006). Our argument aims at proposing new theoretical frameworks for these topics (especially for the former) based on FDPs, rather than providing some concrete and practical results on the topics. We also give some examples of mathematical discussions on FDPs, which would be of independent interest from mathematical viewpoints. Finally, we discuss possible directions of future research on other crypto-graphic applications of FDPs and on mathematical studies on FDPs themselves.

scholarly journals Model Quality Assessment Method Based on Support Vector Machine

2021 ◽  
Vol 25 (1) ◽  
pp. 35-39
Author(s):  
Łukasz Glodek ◽  
Szymon Bysko ◽  
Witold Nocoń
Keyword(s):  
Support Vector Machine ◽  
Quality Assessment ◽  
Industry 4.0 ◽  
Assessment Method ◽  
Support Vector ◽  
Model Quality ◽  
Digital Twin ◽  
Model Quality Assessment ◽  
Virtual Commissioning ◽  
Quality Assessment Method

This paper proposes a model quality assessment method based on Support Vector Machine, which can be used to develop a digital twin. This work is strongly connected with Industry 4.0, in which the main idea is to integrate machines, devices, systems, and IT. One of the goals of Industry 4.0 is to introduce flexible assortment changes. Virtual commissioning can be used to create a simulation model of a plant or conduct training for maintenance engineers. On a branch of virtual commissioning is a digital twin. The digital twin is a virtual representation of a plant or a device. Thanks to the digital twin, different scenarios can be analyzed to make the testing process less complicated and less time-consuming. The goal of this work is to propose a coefficient that will take into account expert knowledge and methods used for model quality assessment (such as Normalized Root Mean Square Error – NRMSE, Maximum Error – ME). NRMSE and ME methods are commonly used for this purpose, but they have not been used simultaneously so far. Each of them takes into consideration another aspect of a model. The coefficient allows deciding whether the model can be used for digital twin appliances. Such an attitude introduces the ability to test models automatically or in a semi-automatic way.

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