scholarly journals Secure File/Data Transfer Between Airgap Network

2021 ◽  
pp. 149-155
Author(s):  
Arathi Navaneeth ◽  
Vignesh P P ◽  
Sreehari N R ◽  
K. Pramilarani
Keyword(s):  
Image Processing ◽  
Data Storage ◽  
Data Privacy ◽  
Data Communication ◽  
Computer Training ◽  
Training Dataset ◽  
Computer Data ◽  
Automatic Data ◽  
Rsa Algorithm ◽  
Confidential Data

Wireless Data communication is fastest growing technology era in which the research society has recently embarked. Today, Computer data can include financial transactions such as electronic payments, M- wallets and sensitive multimedia contents. The explosive volumes of computer devices personal data, bring-up more attention to securely data storage rather than consideration on data privacy and confidentiality levels. In this scenario Air Gap Data Communication, Machine Leaning (ML) and image processing brings an important role in the electronic data management. It is always expensive and hard to manage the data manually without adopting machine learning and image processing techniques using metadata. The contribution of this research article is to demonstrate a securing computer data storage secrecy and privacy in cloud communication framework in terms of automatic data classification using computer training datasets with help of Training dataset which classifies the data based on the confidentiality level of the record with higher accuracy and powerful timelines as compared to the traditional KNN algorithms and RSA algorithm securing such confidential data category afterwards by applying various existing cryptographic solutions to assuring data privacy, confidentiality levels and alerting the use of abusive contents and simulation results demonstrates that reducing the overall cost. Training dataset which classifies the data based on the confidentiality level of the record with higher accuracy and powerful timelines as compared to the traditional KNN algorithms and RSA algorithm securing such confidential data category.

Image processing algorithm for detection, quantification and classification of microdefects in wire electric discharge machined precision finish cut surfaces

2021 ◽  
pp. 251659842110154
Author(s):  
P. M. Abhilash ◽  
D. Chakradhar
Keyword(s):  
Image Processing ◽  
Electric Discharge ◽  
Input Parameter ◽  
Processing Algorithm ◽  
Training Dataset ◽  
Data Generation ◽  
Image Processing Algorithm ◽  
Machined Surface ◽  
Automatic Data ◽  
Finish Cut

This study aims to create an image processing algorithm that categorises the wire electric discharge machine (WEDM) processed finish cut surfaces, based on surface microdefects. The algorithm also detects the defect locations and suggests alternate parameter settings for improving the surface integrity. The proposed automated analysis is more precise, efficient and repeatable compared to manual inspection. Also, the method can be used for automatic data generation to suggest parameter changes in closed loop systems. During the training phase, mean, standard deviation and defect area fraction of enhanced binary images are extracted and stored. The training dataset consists of 27 WEDM finish cut surface images with labels, ‘coarse’, ‘average’ and ‘smooth’. The trained model is capable of categorising any machined surface by detecting the microdefects. If the machined surface image is not classified as a smooth image, then alternate input parameter settings will be suggested by the model to minimise the microdefects. This is done based on the Euclidean distance between the current image datapoint and the nearest ‘smooth’ class datapoint.

Enhanced Security for Electronic Health Care Information Using Obfuscation and RSA Algorithm in Cloud Computing

2019 ◽  
Vol 13 (1) ◽  
pp. 59-69 ◽  
Author(s):  
Pratiksha Gautam ◽  
Mohd. Dilshad Ansari ◽  
Surender Kumar Sharma
Keyword(s):  
Cloud Computing ◽  
Cloud Storage ◽  
Data Privacy ◽  
Health Care Information ◽  
Data Confidentiality ◽  
Rsa Algorithm ◽  
Confidential Data ◽  
Security Properties ◽  
Care Information ◽  
Low Costs

Recently, the electronic heath record (EHR) has become the chosen method to maintain a patient's health information. The advancement of cloud computing enables users to access their data with flexibility, providing large storage capability at low costs, which encourages EHR maintainers to consider shifting from their own storage to the cloud. In cloud computing, it is no doubt that securing EHRs poses a gigantic challenge. Various security properties like access control, data privacy, and scalable access between different clouds needs to be satisfied. This article presents a secure and efficient blueprint for securing data confidentiality on cloud computing storage. The proposed framework is carried out for EHR confidential data on cloud storage. Moreover, the proposed approach combines the obfuscation and RSA encryption together to enforce confidentiality and authentication. Through this framework, the data confidentiality and authentication scheme on EHR information can be enforced on clouds storage.

Enhanced Security for Electronic Health Care Information Using Obfuscation and RSA Algorithm in Cloud Computing

2021 ◽  
pp. 944-956
Author(s):  
Pratiksha Gautam ◽  
Mohd. Dilshad Ansari ◽  
Surender Kumar Sharma
Keyword(s):  
Health Care ◽  
Cloud Computing ◽  
Data Privacy ◽  
Health Care Information ◽  
Data Confidentiality ◽  
Rsa Algorithm ◽  
Confidential Data ◽  
Security Properties ◽  
Care Information ◽  
Low Costs

Recently, the electronic heath record (EHR) has become the chosen method to maintain a patient's health information. The advancement of cloud computing enables users to access their data with flexibility, providing large storage capability at low costs, which encourages EHR maintainers to consider shifting from their own storage to the cloud. In cloud computing, it is no doubt that securing EHRs poses a gigantic challenge. Various security properties like access control, data privacy, and scalable access between different clouds needs to be satisfied. This article presents a secure and efficient blueprint for securing data confidentiality on cloud computing storage. The proposed framework is carried out for EHR confidential data on cloud storage. Moreover, the proposed approach combines the obfuscation and RSA encryption together to enforce confidentiality and authentication. Through this framework, the data confidentiality and authentication scheme on EHR information can be enforced on clouds storage.

scholarly journals A Cloud Game-Based Educative Platform Architecture: The CyberScratch Project

2021 ◽  
Vol 11 (2) ◽  
pp. 807
Author(s):  
Llanos Tobarra ◽  
Alejandro Utrilla ◽  
Antonio Robles-Gómez ◽  
Rafael Pastor-Vargas ◽  
Roberto Hernández
Keyword(s):  
Data Storage ◽  
Data Privacy ◽  
Data Science ◽  
Critical Issue ◽  
Privacy Management ◽  
Instructional Process ◽  
Legal Context ◽  
Flexible Architecture ◽  
Efficient Data ◽  
Implementation Guidelines

The employment of modern technologies is widespread in our society, so the inclusion of practical activities for education has become essential and useful at the same time. These activities are more noticeable in Engineering, in areas such as cybersecurity, data science, artificial intelligence, etc. Additionally, these activities acquire even more relevance with a distance education methodology, as our case is. The inclusion of these practical activities has clear advantages, such as (1) promoting critical thinking and (2) improving students’ abilities and skills for their professional careers. There are several options, such as the use of remote and virtual laboratories, virtual reality and game-based platforms, among others. This work addresses the development of a new cloud game-based educational platform, which defines a modular and flexible architecture (using light containers). This architecture provides interactive and monitoring services and data storage in a transparent way. The platform uses gamification to integrate the game as part of the instructional process. The CyberScratch project is a particular implementation of this architecture focused on cybersecurity game-based activities. The data privacy management is a critical issue for these kinds of platforms, so the architecture is designed with this feature integrated in the platform components. To achieve this goal, we first focus on all the privacy aspects for the data generated by our cloud game-based platform, by considering the European legal context for data privacy following GDPR and ISO/IEC TR 20748-1:2016 recommendations for Learning Analytics (LA). Our second objective is to provide implementation guidelines for efficient data privacy management for our cloud game-based educative platform. All these contributions are not found in current related works. The CyberScratch project, which was approved by UNED for the year 2020, considers using the xAPI standard for data handling and services for the game editor, game engine and game monitor modules of CyberScratch. Therefore, apart from considering GDPR privacy and LA recommendations, our cloud game-based architecture covers all phases from game creation to the final users’ interactions with the game.

scholarly journals Secure Framework Enhancing AES Algorithm in Cloud Computing

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Ijaz Ahmad Awan ◽  
Muhammad Shiraz ◽  
Muhammad Usman Hashmi ◽  
Qaisar Shaheen ◽  
Rizwan Akhtar ◽  
...  
Keyword(s):  
Data Privacy ◽  
Security Threats ◽  
Privacy And Security ◽  
Plain Text ◽  
Aes Algorithm ◽  
Confidential Data ◽  
Network Usage ◽  
Data Centres ◽  
Demand Service ◽  
Remote Data

The tremendous growth of computational clouds has attracted and enabled intensive computation on resource-constrained client devices. Predominantly, smart mobiles are enabled to deploy data and computational intensive applications by leveraging on the demand service model of remote data centres. However, outsourcing personal and confidential data to the remote data servers is challenging for the reason of new issues involved in data privacy and security. Therefore, the traditional advanced encryption standard (AES) algorithm needs to be enhanced in order to cope with the emerging security threats in the cloud environment. This research presents a framework with key features including enhanced security and owner’s data privacy. It modifies the 128 AES algorithm to increase the speed of the encryption process, 1000 blocks per second, by the double round key feature. However, traditionally, there is a single round key with 800 blocks per second. The proposed algorithm involves less power consumption, better load balancing, and enhanced trust and resource management on the network. The proposed framework includes deployment of AES with 16, 32, 64, and 128 plain text bytes. Simulation results are visualized in a way that depicts suitability of the algorithm while achieving particular quality attributes. Results show that the proposed framework minimizes energy consumption by 14.43%, network usage by 11.53%, and delay by 15.67%. Hence, the proposed framework enhances security, minimizes resource utilization, and reduces delay while deploying services of computational clouds.

PpBAC

2018 ◽  
Vol 30 (4) ◽  
pp. 14-31 ◽  
Author(s):  
Suyel Namasudra ◽  
Pinki Roy
Keyword(s):  
Cloud Computing ◽  
Access Control ◽  
Data Storage ◽  
Control Method ◽  
Cloud Environment ◽  
Authorized User ◽  
Control Scheme ◽  
Control Schemes ◽  
Confidential Data ◽  
Efficient Data

This article describes how nowadays, cloud computing is one of the advanced areas of Information Technology (IT) sector. Since there are many hackers and malicious users on the internet, it is very important to secure the confidentiality of data in the cloud environment. In recent years, access control has emerged as a challenging issue of cloud computing. Access control method allows data accessing of an authorized user. Existing access control schemes mainly focus on the confidentiality of the data storage. In this article, a novel access control scheme has been proposed for efficient data accessing. The proposed scheme allows reducing the searching cost and accessing time, while providing the data to the user. It also maintains the security of the user's confidential data.

scholarly journals XML-based IUPAC standard for experimental, predicted, and critically evaluated thermodynamic property data storage and capture (ThermoML) (IUPAC Recommendations 2006)

2006 ◽  
Vol 78 (3) ◽  
pp. 541-612 ◽  
Author(s):  
Michael Frenkel ◽  
Robert D. Chiroco ◽  
Vladimir Diky ◽  
Qian Dong ◽  
Kenneth N. Marsh ◽  
...  
Keyword(s):  
Data Storage ◽  
Chemical Reactions ◽  
Data Communication ◽  
Thermochemical Property ◽  
Uncertainty In Measurement ◽  
Communication Processes ◽  
Property Data ◽  
Extensible Markup ◽  
Pure Compounds ◽  
Expression Of Uncertainty

ThermoML is an Extensible Markup Language (XML)-based new IUPAC standard for storage and exchange of experimental, predicted, and critically evaluated thermophysical and thermochemical property data. The basic principles, scope, and description of all structural elements of ThermoML are discussed. ThermoML covers essentially all thermodynamic and transport property data (more than 120 properties) for pure compounds, multicomponent mixtures, and chemical reactions (including change-of-state and equilibrium reactions). Representations of all quantities related to the expression of uncertainty in ThermoML conform to the Guide to the Expression of Uncertainty in Measurement (GUM). The ThermoMLEquation schema for representation of fitted equations with ThermoML is also described and provided as supporting information together with specific formulations for several equations commonly used in the representation of thermodynamic and thermophysical properties. The role of ThermoML in global data communication processes is discussed. The text of a variety of data files (use cases) illustrating the ThermoML format for pure compounds, mixtures, and chemical reactions, as well as the complete ThermoML schema text, are provided as supporting information.

scholarly journals Computer Data Storage and Management Platform Based on Big Data

2021 ◽  
Vol 2066 (1) ◽  
pp. 012022
Author(s):  
Cheng Luo
Keyword(s):  
Big Data ◽  
Data Management ◽  
Performance Improvement ◽  
Data Storage ◽  
Nonvolatile Memory ◽  
Linear Structure ◽  
Ring Structure ◽  
Computer Data ◽  
Management Platform ◽  
A Performance

Abstract Due to the continuous development of information technology, data has increasingly become the core of the daily operation of enterprises and institutions, the main basis for decision-making development. At the same time, due to the development of network, the storage and management of computer data has attracted more and more attention. Aiming at the common problems of computer data storage and management in practical work, this paper analyzes the object and content of data management, investigates the situation of computer data storage and management in China in recent two years, and interviews and tests the data of programming in this design platform. At the same time, in view of the related problems, the research results are applied to practice. On the basis of big data, the storage and management platform is designed. The research and design adopts a special B+ tree node linear structure of CIRC tree, and the linear node structure is changed into a ring structure, which greatly reduces the number of data persistence instructions and the performance overhead. The results show that compared with the most advanced B+ tree design for nonvolatile memory, crab tree has 3.1 times and 2.5 times performance improvement in reading and writing, respectively. Compared with the previous NV tree designed for nonvolatile memory, it has a performance improvement of 1.5 times, and a performance improvement of 8.4 times compared with the latest fast-fair. In the later stage, the expansion of the platform functions is conducive to the analysis and construction of data related storage and management functions, and further improve the ability of data management.

scholarly journals Design of a Machine Learning-Based Intelligent Middleware Platform for a Heterogeneous Private Edge Cloud System

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7701
Author(s):  
Sayed-Chhattan Shah
Keyword(s):  
Machine Learning ◽  
Data Storage ◽  
Smart City ◽  
Data Privacy ◽  
Mobile Technologies ◽  
Cloud System ◽  
Multilayer Network ◽  
Network Applications ◽  
Data Rates ◽  
5G Network

Recent advances in mobile technologies have facilitated the development of a new class of smart city and fifth-generation (5G) network applications. These applications have diverse requirements, such as low latencies, high data rates, significant amounts of computing and storage resources, and access to sensors and actuators. A heterogeneous private edge cloud system was proposed to address the requirements of these applications. The proposed heterogeneous private edge cloud system is characterized by a complex and dynamic multilayer network and computing infrastructure. Efficient management and utilization of this infrastructure may increase data rates and reduce data latency, data privacy risks, and traffic to the core Internet network. A novel intelligent middleware platform is proposed in the current study to manage and utilize heterogeneous private edge cloud infrastructure efficiently. The proposed platform aims to provide computing, data collection, and data storage services to support emerging resource-intensive and non-resource-intensive smart city and 5G network applications. It aims to leverage regression analysis and reinforcement learning methods to solve the problem of efficiently allocating heterogeneous resources to application tasks. This platform adopts parallel transmission techniques, dynamic interface allocation techniques, and machine learning-based algorithms in a dynamic multilayer network infrastructure to improve network and application performance. Moreover, it uses container and device virtualization technologies to address problems related to heterogeneous hardware and execution environments.

Sign in / Sign up

Export Citation Format

Share Document