Research on Network Security Analysis Based on Big Data Technology Application

Abstract Background As COVID-19 continues to spread globally, traditional emergency management measures are facing many practical limitations. The application of big data analysis technology provides an opportunity for local governments to conduct the COVID-19 epidemic emergency management more scientifically. The present study, based on emergency management lifecycle theory, includes a comprehensive analysis of the application framework of China’s SARS epidemic emergency management lacked the support of big data technology in 2003. In contrast, this study first proposes a more agile and efficient application framework, supported by big data technology, for the COVID-19 epidemic emergency management and then analyses the differences between the two frameworks. Methods This study takes Hainan Province, China as its case study by using a file content analysis and semistructured interviews to systematically comprehend the strategy and mechanism of Hainan’s application of big data technology in its COVID-19 epidemic emergency management. Results Hainan Province adopted big data technology during the four stages, i.e., migration, preparedness, response, and recovery, of its COVID-19 epidemic emergency management. Hainan Province developed advanced big data management mechanisms and technologies for practical epidemic emergency management, thereby verifying the feasibility and value of the big data technology application framework we propose. Conclusions This study provides empirical evidence for certain aspects of the theory, mechanism, and technology for local governments in different countries and regions to apply, in a precise, agile, and evidence-based manner, big data technology in their formulations of comprehensive COVID-19 epidemic emergency management strategies.

Download Full-text

Advanced Network Security Analysis (ANSA) in Big Data Technology

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.j9369.0881019 ◽

2019 ◽

Vol 8 (10) ◽

pp. 2634-2639

Keyword(s):

Big Data ◽

Security Analysis ◽

Traffic Classification ◽

Network Attacks ◽

Business World ◽

Hadoop Distributed File System ◽

Data Environment ◽

The Internet Of Things ◽

Activity Information ◽

Big Data Technology

Big Data has caught the attention of research, science, and business world due to the advancement in digitalization. With the evolution of the Internet of Things (IoT), data is increasing by massive amounts every day. In the big data environment, securing a large amount of data has become a challenging issue in both security and research industry. In this paper, a framework has been proposed to inspect malignant information and suspicious activities traveling over the networks by utilizing Hive Queries. This framework’s procedure loads activity information into Hadoop Distributed File System (HDFS) through a Hive database thus examining the information. This information is sorted as IP Wise, Port Wise, and Protocol Wise. Hive queries will help to achieve these three goals:- 1) Traffic classification 2) Interrupt Identification 3) analyzing of network traffic. Using this framework provides users’ a benefit of being able to investigate Big Data and helps them to detect attacks. Therefore, this framework will allow prevention of network attacks and enable real-time detection in a Big Data environment.

Download Full-text

BI warehousing system based on big data

E3S Web of Conferences ◽

10.1051/e3sconf/202125702015 ◽

2021 ◽

Vol 257 ◽

pp. 02015

Author(s):

Xiangming Lin ◽

Kai Liu ◽

Yixuan Li

Keyword(s):

Big Data ◽

Rapid Development ◽

Reference Value ◽

Data Management System ◽

System Construction ◽

Technology Application ◽

Detailed Explanation ◽

Warehousing Systems ◽

Big Data Technology

In the wave of informatization, the data generated by enterprise operations has increased rapidly, prompting the intelligent development of enterprise warehousing systems. In the development of BI warehousing systems, the application of big data technology can promote the rapid development of business intelligence warehousing systems. The application of big data technology in the BI warehousing system can improve the service quality of the data intelligence of the warehousing system. Based on data, it provides support for corresponding decision-making, thereby improving the enterprise data management system. Therefore, this article mainly conducts research and analysis on the construction of BI warehousing system under the application of big data technology, and aims to provide a certain reference value for similar events in the future through a detailed explanation of the current situation of BI warehousing system construction and big data technology application.

Download Full-text

Research on Real Estate Information System of the Real Estate Market Based on Big Data Technology

E3S Web of Conferences ◽

10.1051/e3sconf/202125702037 ◽

2021 ◽

Vol 257 ◽

pp. 02037

Author(s):

Benli Li

Keyword(s):

Information System ◽

Big Data ◽

Real Estate ◽

Real Estate Market ◽

Design System ◽

Technology Application ◽

The Real ◽

The Real Estate ◽

The Real Estate Market ◽

Big Data Technology

This article analyzes and studies the importance of establishing a real estate information system in the real estate market. The research content of this article includes improving the efficiency of data utilization, formulating the important support of marketing strategy, and the inevitable trend of marketing system reform. The author studies the system technical route analysis, functional module design, logical hierarchical structure design, overall database design, data collection and storage method design, system key technology application, etc. The purpose of this article is to improve the applicability of information systems to regional development and to enhance the use value of big data technology itself.

Download Full-text