Data Security and Validation Framework for a Scientific Data Processing SOA Based System

2011 ◽  
Author(s):  
Veska Gancheva
Keyword(s):  
Data Processing ◽  
Data Security ◽  
Scientific Data ◽  
Validation Framework

scholarly journals THE GWAC DATA PROCESSING AND MANAGEMENT SYSTEM

2021 ◽  
Vol 53 ◽  
pp. 174-179
Author(s):  
Y. Xu ◽  
L. P. Xin ◽  
X. H. Han ◽  
H. B. Cai ◽  
L. Huang ◽  
...  
Keyword(s):  
Data Processing ◽  
User Interfaces ◽  
Management System ◽  
Scientific Data ◽  
Data Archiving ◽  
Processing Pipeline ◽  
Advanced Technologies ◽  
Single Frame ◽  
Moonless Night ◽  
Processing Requirement

GWAC will have been built an integrated FOV of 5,000 degree2 and have already built 1,800 square degree2. The limit magnitude of a 10-second exposure image in the moonless night is 16R. In each observation night, GWAC produces about 0.7TB of raw data, and the data processing pipeline generates millions of single frame alerts. We describe the GWAC Data Processing and Management System (GPMS), including hardware architecture, database, detection-filtering-validation of transient candidates, data archiving, and user interfaces for the check of transient and the monitor of the system. GPMS combines general technology and software in astronomy and computer field, and use some advanced technologies such as deep learning. Practical results show that GPMS can fully meet the scientific data processing requirement of GWAC. It can online accomplish the detection, filtering and validation of millions of transient candidates, and feedback the final results to the astronomer in real-time. During the observation from October of 2018 to December of 2019, we have already found 102 transients.

scholarly journals A scientific data processing framework for time series NetCDF data

2014 ◽  
Vol 60 ◽  
pp. 241-249 ◽  
Author(s):  
Krista Gaustad ◽  
Tim Shippert ◽  
Brian Ermold ◽  
Sherman Beus ◽  
Jeff Daily ◽  
...  
Keyword(s):  
Time Series ◽  
Data Processing ◽  
Scientific Data ◽  
Processing Framework

scholarly journals Gaia: Astrometric performance and current status of the project

2009 ◽  
Vol 5 (S261) ◽  
pp. 296-305 ◽  
Author(s):  
Lennart Lindegren
Keyword(s):  
Solar System ◽  
Data Processing ◽  
Preliminary Data ◽  
Scientific Data ◽  
Current Status ◽  
Fundamental Physics ◽  
Implementation Phase ◽  
Optical Reference ◽  
Measurement Principle

AbstractThe scientific objectives of the Gaia mission cover areas of galactic structure and evolution, stellar astrophysics, exoplanets, solar system physics, and fundamental physics. Astrometrically, its main contribution will be the determination of millions of absolute stellar parallaxes and the establishment of a very accurate, dense and faint non-rotating optical reference frame. With a planned launch in spring 2012, the project is in its advanced implementation phase. In parallel, preparations for the scientific data processing are well under way within the Gaia Data Processing and Analysis Consortium. Final mission results are expected around 2021, but early releases of preliminary data are expected. This review summarizes the main science goals and overall organisation of the project, the measurement principle and core astrometric solution, and provide an updated overview of the expected astrometric performance.

Protein Experiment: Scientific Data Processing Platform for On-Flight Experiment Tuning

2012 ◽  
Vol 24 (5) ◽  
pp. 327-334 ◽  
Author(s):  
Luis David Patiño-Lopez ◽  
Klaas Decanniere ◽  
Jose Antonio Gavira ◽  
Dominique Maes ◽  
Fermín Otalora
Keyword(s):  
Data Processing ◽  
Scientific Data ◽  
Flight Experiment ◽  
Processing Platform

Exploring the Data Processing Practices of Cloud ERP—A Case Study

2019 ◽  
Vol 17 (1) ◽  
pp. 63-70 ◽  
Author(s):  
Lei Gao
Keyword(s):  
Data Processing ◽  
Enterprise Resource Planning ◽  
Data Security ◽  
Resource Planning ◽  
Erp Systems ◽  
Case Study Method ◽  
Data Confidentiality ◽  
Data Retention ◽  
Data Process

ABSTRACT Although cloud enterprise resource planning (ERP) systems are becoming popular, there are still firms that have yet to migrate to the cloud because of data confidentiality and data security concerns. Firms that plan to adopt cloud ERP systems are expected to first understand cloud ERP's data processing practices. This study proposes a case study method with a systematic content analysis of cloud ERP providers' data processing agreements. The study will explore the data disclosure, data security, data sub-processing, and data retention and deletion practices of cloud ERP providers. In addition, this study investigates the linguistic characteristics of cloud ERP providers' data processing agreements including readability, litigious language, and uncertainty language. The findings of this study can help organizations to have a better understanding of the data process practices of cloud ERP providers, as well as the shared responsibilities between cloud ERP providers and users in maintaining data security.

scholarly journals High-Efficiency Parallel Cryptographic Accelerator for Real-Time Guaranteeing Dynamic Data Security in Embedded Systems

Micromachines ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 560
Author(s):  
Zhun Zhang ◽  
Xiang Wang ◽  
Qiang Hao ◽  
Dongdong Xu ◽  
Jinlei Zhang ◽  
...  
Keyword(s):  
Embedded Systems ◽  
Data Processing ◽  
Data Security ◽  
Data Exchange ◽  
High Efficiency ◽  
Main Memory ◽  
Processing Efficiency ◽  
Dynamic Data ◽  
Field Programmable ◽  
On Chip

Dynamic data security in embedded systems is raising more and more concerns in numerous safety-critical applications. In particular, the data exchanges in embedded Systems-on-Chip (SoCs) using main memory are exposing many security vulnerabilities to external attacks, which will cause confidential information leakages and program execution failures for SoCs at key points. Therefore, this paper presents a security SoC architecture with integrating a four-parallel Advanced Encryption Standard-Galois/Counter Mode (AES-GCM) cryptographic accelerator for achieving high-efficiency data processing to guarantee data exchange security between the SoC and main memory against bus monitoring, off-line analysis, and data tampering attacks. The architecture design has been implemented and verified on a Xilinx Virtex-5 Field Programmable Gate Array (FPGA) platform. Based on evaluation of the cryptographic accelerator in terms of performance overhead, security capability, processing efficiency, and resource consumption, experimental results show that the parallel cryptographic accelerator does not incur significant performance overhead on providing confidentiality and integrity protections for exchanged data; its average performance overhead reduces to as low as 2.65% on typical 8-KB I/D-Caches, and its data processing efficiency is around 3 times that of the pipelined AES-GCM construction. The reinforced SoC under the data tampering attacks and benchmark tests confirms the effectiveness against external physical attacks and satisfies a good trade-off between high-efficiency and hardware overhead.

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