scholarly journals Application of hierarchic authentication to isogenies of elliptic curves for providing safety of data routing in the systems of analysis of digital production traffic

2018 ◽  
Vol 44 ◽  
pp. 00007
Author(s):  
Elena Alexandrova ◽  
Maria Poltavtseva ◽  
Anastasia Yarmak
Keyword(s):  
Big Data ◽  
Information Processing ◽  
Elliptic Curves ◽  
Traffic Analysis ◽  
Quantum Systems ◽  
Data Routing ◽  
Digital Production ◽  
A Chain

The article discusses the peculiarities of the process of information routing in the course of acquisition and processing big data of digital production, including systems of traffic analysis. Such a specific features variability of physical nodes-processors with the retention of functional stringency of order of information processing is distinguished. Inordertoprovidesafetyofthedescribedprocessofinformationprocessingand possibility of restoration of a chain of processing every fragment of data, the authors offer a protocol of hierarchic authentication developed thereby on isogenies of elliptic curves. The work includes algorithms of shaping parameters, generation of keys, generation and checking signature. The evaluation of signature stability again basic types of attacks has been performed. A solution offered by the authors can be used both in traditional and, in future, in quantum systems. A simulation of corresponding signature dimensions has been performed in the work.

scholarly journals Perturbation Analysis of Quantum Reset Models

2021 ◽  
Vol 183 (1) ◽  
Author(s):  
Géraldine Haack ◽  
Alain Joye
Keyword(s):  
Steady State ◽  
Perturbation Analysis ◽  
Open Quantum Systems ◽  
Quantum Systems ◽  
Markov Semigroup ◽  
Coupling Constant ◽  
Coupling Term ◽  
Open Quantum ◽  
Effective Dynamics ◽  
A Chain

AbstractThis paper is devoted to the analysis of Lindblad operators of Quantum Reset Models, describing the effective dynamics of tri-partite quantum systems subject to stochastic resets. We consider a chain of three independent subsystems, coupled by a Hamiltonian term. The two subsystems at each end of the chain are driven, independently from each other, by a reset Lindbladian, while the center system is driven by a Hamiltonian. Under generic assumptions on the coupling term, we prove the existence of a unique steady state for the perturbed reset Lindbladian, analytic in the coupling constant. We further analyze the large times dynamics of the corresponding CPTP Markov semigroup that describes the approach to the steady state. We illustrate these results with concrete examples corresponding to realistic open quantum systems.

Research of wireless network traffic analysis using big data processing technology

2021 ◽  
Author(s):  
Kovtsur Maxim ◽  
Kistruga Anton ◽  
Mikhailova Anastasiya ◽  
Potemkin Pavel ◽  
Volkogonov Vladimir
Keyword(s):  
Big Data ◽  
Data Processing ◽  
Wireless Network ◽  
Network Traffic ◽  
Traffic Analysis ◽  
Processing Technology ◽  
Big Data Processing ◽  
Network Traffic Analysis

New Trends in Databases to NonSQL Databases

2021 ◽  
pp. 791-799
Author(s):  
Antonio Sarasa-Cabezuelo
Keyword(s):  
Big Data ◽  
Information Processing ◽  
Real Time ◽  
Relational Databases ◽  
Data Models ◽  
Relational Model ◽  
Alternative Mechanism ◽  
New Models ◽  
Database Models

The appearance of the “big data” phenomenon has meant a change in the storage and information processing needs. This new context is characterized by 1) enormous amounts of information are available in heterogeneous formats and types, 2) information must be processed almost in real time, and 3) data models evolve periodically. Relational databases have limitations to respond to these needs in an optimal way. For these reasons, some companies such as Google or Amazon decided to create new database models (different from the relational model) that solve the needs raised in the context of big data without the limitations of relational databases. These new models are the origin of the so-called NonSQL databases. Currently, NonSQL databases have been constituted as an alternative mechanism to the relational model and its use is widely extended. The main objective of this chapter is to introduce the NonSQL databases.

scholarly journals Creating Sustainable Innovativeness through Big Data and Big Data Analytics Capability: From the Perspective of the Information Processing Theory

2020 ◽  
Vol 12 (5) ◽  
pp. 1984
Author(s):  
Michael Song ◽  
Haili Zhang ◽  
Jinjin Heng
Keyword(s):  
Big Data ◽  
Information Processing ◽  
Data Analytics ◽  
Big Data Analytics ◽  
The United States ◽  
Information Processing Theory ◽  
Processing Theory ◽  
Study Results ◽  
Analytics Capability ◽  
Cross National

Service innovativeness is a key sustainable competitive advantage that increases sustainability of enterprise development. Literature suggests that big data and big data analytics capability (BDAC) enhance sustainable performance. Yet, no studies have examined how big data and BDAC affect service innovativeness. To fill this research gap, based on the information processing theory (IPT), we examine how fits and misfits between big data and BDAC affect service innovativeness. To increase cross-national generalizability of the study results, we collected data from 1403 new service development (NSD) projects in the United States, China and Singapore. Dummy regression method was used to test the model. The results indicate that for all three countries, high big data and high BDAC has the greatest effect on sustainable innovativeness. In China, fits are always better than misfits for creating sustainable innovativeness. In the U.S., high big data is always better for increasing sustainable innovativeness than low big data is. In contrast, in Singapore, high BDAC is always better for enhancing sustainable innovativeness than low BDAC is. This study extends the IPT and enriches cross-national research of big data and BDAC. We conclude the article with suggestions of research limitations and future research directions.

Cloud data acquisition and processing model based on blockchain

2020 ◽  
Vol 39 (4) ◽  
pp. 5027-5036
Author(s):  
You Lu ◽  
Qiming Fu ◽  
Xuefeng Xi ◽  
Zhenping Chen
Keyword(s):  
Big Data ◽  
Data Structure ◽  
Data Collection ◽  
Cloud Data ◽  
Integrity Verification ◽  
Blockchain Technology ◽  
Verification System ◽  
Using Data ◽  
A Chain ◽  
And Storage

Data outsourcing has gradually become a mainstream solution, but once data is outsourced, data owners will without the control of the data hardware, there is a possibility that the integrity of the data will be destroyed objectively. Many current studies have achieved low network overhead cloud data set verification by designing algorithmic structures (e.g., hashing, Merkel verification trees); however, cloud service providers may not recognize the incompleteness of cloud data to avoid liability or business factors fact. There is a need to build a secure, reliable, non-tamperable, and non-forgeable verification system for accountability. Blockchain is a chain-like data structure constructed by using data signatures, timestamps, hash functions, and proof-of-work mechanisms. Using blockchain technology to build an integrity verification system can achieve fault accountability. Blockchain is a chain-like data structure constructed by using data signatures, timestamps, hash functions, and proof-of-work mechanisms. Using blockchain technology to build an integrity verification system can achieve fault accountability. This paper uses the Hadoop framework to implement data collection and storage of the HBase system based on big data architecture. In summary, based on the research of blockchain cloud data collection and storage technology, based on the existing big data storage middleware, a large flow, high concurrency and high availability data collection and processing system has been realized.

Enabling integrated business planning through big data analytics: a case study on sales and operations planning

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Alexander Schlegel ◽  
Hendrik Sebastian Birkel ◽  
Evi Hartmann
Keyword(s):  
Big Data ◽  
Information Processing ◽  
Data Analytics ◽  
Single Case ◽  
Big Data Analytics ◽  
Business Planning ◽  
Operations Planning ◽  
Content Type ◽  
The Impact

PurposeThe purpose of this study is to investigate how big data analytics capabilities (BDAC) enable the implementation of integrated business planning (IBP) – the advanced form of sales and operations planning (S&OP) – by counteracting the increasing information processing requirements.Design/methodology/approachThe research model is grounded in the organizational information processing theory (OIPT). An embedded single case study on a multinational agrochemical company with multiple geographically distinguished sub-units of analysis was conducted. Data were collected in workshops, semistructured interviews as well as direct observations and enriched by secondary data from internal company sources as well as publicly available sources.FindingsThe results show the relevancy of establishing BDAC within an organization to apply IBP by providing empirical evidence of BDA solutions in S&OP. The study highlights how BDAC increase an organization's information processing capacity and consequently enable efficient and effective S&OP. Practical guidance toward the development of tangible, human and intangible BDAC in a particular sequence is given.Originality/valueThis study is the first theoretically grounded, empirical investigation of S&OP implementation journeys under consideration of the impact of BDAC.

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