scholarly journals Artificial Intelligence- (AI-) Enabled Internet of Things (IoT) for Secure Big Data Processing in Multihoming Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Geetanjali Rathee ◽  
Adel Khelifi ◽  
Razi Iqbal
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Data Processing ◽  
Secure Communication ◽  
Security Risk ◽  
Huge Amount ◽  
Big Data Processing ◽  
Security Issues ◽  
Real Time Analysis ◽  
Artificial Network

The automated techniques enabled with Artificial Neural Networks (ANN), Internet of Things (IoT), and cloud-based services affect the real-time analysis and processing of information in a variety of applications. In addition, multihoming is a type of network that combines various types of networks into a single environment while managing a huge amount of data. Nowadays, the big data processing and monitoring in multihoming networks provide less attention while reducing the security risk and efficiency during processing or monitoring the information. The use of AI-based systems in multihoming big data with IoT- and AI-integrated systems may benefit in various aspects. Although multihoming security issues and their analysis have been well studied by various scientists and researchers; however, not much attention is paid towards big data security processing in multihoming especially using automated techniques and systems. The aim of this paper is to propose an IoT-based artificial network to process and compute big data processing by ensuring a secure communication multihoming network using the Bayesian Rule (BR) and Levenberg-Marquardt (LM) algorithms. Further, the efficiency and effect on multihoming information processing using an AI-assisted mechanism are experimented over various parameters such as classification accuracy, classification time, specificity, sensitivity, ROC, and F -measure.

Trends and Technologies in Big Data Processing

2020 ◽  
pp. 17-42
Author(s):  
Amitava Choudhury ◽  
Kalpana Rangra
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Internet Of Things ◽  
Data Processing ◽  
Real Time ◽  
Computing Technology ◽  
Time Data ◽  
Big Data Processing ◽  
Real Time Data ◽  
Real Time Data Processing

Data type and amount in human society is growing at an amazing speed, which is caused by emerging new services such as cloud computing, internet of things, and location-based services. The era of big data has arrived. As data has been a fundamental resource, how to manage and utilize big data better has attracted much attention. Especially with the development of the internet of things, how to process a large amount of real-time data has become a great challenge in research and applications. Recently, cloud computing technology has attracted much attention to high performance, but how to use cloud computing technology for large-scale real-time data processing has not been studied. In this chapter, various big data processing techniques are discussed.

scholarly journals Text And Sentimental Analysis On Big Data

2021 ◽  
pp. 324-334
Author(s):  
Saifuzzafar Jaweed Ahmed
Keyword(s):  
Big Data ◽  
Data Processing ◽  
Virtual Machines ◽  
Heterogeneous Data ◽  
Machine Learning Algorithms ◽  
Unstructured Data ◽  
Large Field ◽  
Huge Amount ◽  
Data Set ◽  
Big Data Processing

Big Data has become a very important part of all industries and organizations sectors nowadays. All sectors like energy, banking, retail, hardware, networking, etc all generate a huge amount of unstructured data which is processed and analyzed accurately in a structured form. Then the structured data can reveal very useful information for their business growth. Big Data helps in getting useful data from unstructured or heterogeneous data by analyzing them. Big data initially defined by the volume of a data set. Big data sets are generally huge, measuring tens of terabytes and sometimes crossing the sting of petabytes. Today, big data falls under three categories structured, unstructured, and semi-structured. The size of big data is improving in a fast phase from Terabytes to Exabytes Of data. Also, Big data requires techniques that help to integrate a huge amount of heterogeneous data and to process them. Data Analysis which is a big data process has its applications in various areas such as business processing, disease prevention, cybersecurity, and so on. Big data has three major issues such as data storage, data management, and information retrieval. Big data processing requires a particular setup of hardware and virtual machines to derive results. The processing is completed simultaneously to realize results as quickly as possible. These days big data processing techniques include Text mining and sentimental analysis. Text analytics is a very large field under which there are several techniques, models, methods for automatic and quantitative analysis of textual data. The purpose of this paper is to show how the text analysis and sentimental analysis process the unstructured data and how these techniques extract meaningful information and, thus make information available to the various data mining statistical and machine learning) algorithms.

Challenges and Solutions of Big Data and IoT

2019 ◽  
pp. 264-272
Author(s):  
Jayashree K. ◽  
Abirami R. ◽  
Rajeswari P.
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Collection ◽  
Internet Of Things ◽  
Data Processing ◽  
The Internet ◽  
Huge Amount ◽  
Collection Data ◽  
Different Sources ◽  
The Internet Of Things

The successful development of big data and the internet of things (IoT) is increasing and influencing all areas of technologies and businesses. The rapid increase of more devices that are connected to IoT from which enormous amount of data are consumed indicates the way how big data is related with IoT. Since huge amount of data are obtained from different sources, analysis of these data involves much of processing at each and every level to extract knowledge for decision making process. To manage big data in a continuous network that keeps expanding leads to few issues related to data collection, data processing, analytics, and security. To address these issues, certain solution using bigdata approach in IoT are examined. Combining these two areas provides several opportunities developing new systems and identify advanced techniques to solve challenges on big data and IoT.

scholarly journals Architecture of the Parallel Big Data Processing System for Security Monitoring of Internet of Things Networks

2018 ◽  
Vol 4 (59) ◽  
pp. 5 ◽  
Author(s):  
Igor Vitalievich Kotenko ◽  
Igor Borisovich Saenko ◽  
Alexey Gennadievich Kushnerevich
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Data Processing ◽  
Processing System ◽  
Data Processing System ◽  
Big Data Processing ◽  
Security Monitoring

scholarly journals A REVIEW ON INTERNET OF THINGS ARCHITECTURE FOR BIG DATA PROCESSING

2020 ◽  
Vol 46 (1) ◽  
pp. 11-19
Author(s):  
Wid Akeel Awadh ◽  
Ali Salah Hashim ◽  
Alaa Khalaf Hamoud
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Data Processing ◽  
Data Transfer ◽  
Security Requirements ◽  
Big Data Processing ◽  
Political Market ◽  
The People ◽  
Gps Satellites ◽  
Social Interests

The importance of big data implementations is increased due to large amount of gathered data via the online gates. The businesses and organizations would benefit from the big data analysis i.e. analyze the political, market, and social interests of the people. The Internet of Things (IoT) presents many facilities that support the big data transfer between various Internet objects. The integration between the big data and IoT offer a lot of implementations in the daily life like GPS, Satellites, and airplanes tracking. There are many challenges face the integration between big data transfer and IoT technology. The main challenges are the transfer architecture, transfer protocols, and the transfer security. The main aim of this paper is to review the useful architecture of IoT for the purpose of big data processing with the consideration of the various requirements such as the transfer protocol. This paper also reviews other important issues such as the security requirements and the multiple IoT applications. In addition, the future directions of the IoT-Big data are explained in this paper.

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