Analysis of Security and Privacy in Public Cloud Environment

2015 ◽  
Author(s):  
Abdul Sattar Raja ◽  
Shukor Abd Razak
Keyword(s):  
Security And Privacy ◽  
Cloud Environment ◽  
Public Cloud

A Review on Load Balancing Model Using Best Partition Technique

2017 ◽  
Vol 7 (8) ◽  
pp. 284
Author(s):  
M. Chaitanya ◽  
K. Durga Charan
Keyword(s):  
Cloud Computing ◽  
Fault Tolerance ◽  
Load Balancing ◽  
Load Balance ◽  
Large Impact ◽  
Cloud Environment ◽  
Public Cloud ◽  
The Public ◽  
Partition Technique ◽  
Textual Content

Load balancing makes cloud computing greater knowledgeable and could increase client pleasure. At reward cloud computing is among the all most systems which offer garage of expertise in very lowers charge and available all the time over the net. However, it has extra vital hassle like security, load administration and fault tolerance. Load balancing inside the cloud computing surroundings has a large impact at the presentation. The set of regulations relates the sport idea to the load balancing manner to amplify the abilties in the public cloud environment. This textual content pronounces an extended load balance mannequin for the majority cloud concentrated on the cloud segregating proposal with a swap mechanism to select specific strategies for great occasions.

scholarly journals A Secure Encrypted Classified Electronic Healthcare Data for Public Cloud Environment

2022 ◽  
Vol 32 (2) ◽  
pp. 765-779
Author(s):  
Kirupa Shankar Komathi Maathavan ◽  
Santhi Venkatraman
Keyword(s):  
Cloud Environment ◽  
Public Cloud ◽  
Healthcare Data

scholarly journals Security and Privacy Risk Assessment of Energy Big Data in Cloud Environment

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Zhiru Li ◽  
Wei Xu ◽  
Huibin Shi ◽  
Yuanyuan Zhang ◽  
Yan Yan
Keyword(s):  
Neural Network ◽  
Risk Factors ◽  
Risk Assessment ◽  
Big Data ◽  
Data Storage ◽  
Bp Neural Network ◽  
Security And Privacy ◽  
Cloud Environment ◽  
Privacy Risk ◽  
Whole Life Cycle

Considering the importance of energy in our lives and its impact on other critical infrastructures, this paper starts from the whole life cycle of big data and divides the security and privacy risk factors of energy big data into five stages: data collection, data transmission, data storage, data use, and data destruction. Integrating into the consideration of cloud environment, this paper fully analyzes the risk factors of each stage and establishes a risk assessment index system for the security and privacy of energy big data. According to the different degrees of risk impact, AHP method is used to give indexes weights, genetic algorithm is used to optimize the initial weights and thresholds of BP neural network, and then the optimized weights and thresholds are given to BP neural network, and the evaluation samples in the database are used to train it. Then, the trained model is used to evaluate a case to verify the applicability of the model.

Centralized Fog Computing Security Platform for IoT and Cloud in Healthcare System

2018 ◽  
pp. 141-154 ◽  
Author(s):  
Chandu Thota ◽  
Revathi Sundarasekar ◽  
Gunasekaran Manogaran ◽  
Varatharajan R ◽  
Priyan M. K.
Keyword(s):  
Healthcare System ◽  
Data Transfer ◽  
Fog Computing ◽  
Asynchronous Communication ◽  
Security And Privacy ◽  
Sensor Data ◽  
Cloud Environment ◽  
Authentication And Authorization ◽  
Remote Healthcare ◽  
Secure Authentication

This chapter proposes an efficient centralized secure architecture for end to end integration of IoT based healthcare system deployed in Cloud environment. The proposed platform uses Fog Computing environment to run the framework. In this chapter, health data is collected from sensors and collected sensor data are securely sent to the near edge devices. Finally, devices transfer the data to the cloud for seamless access by healthcare professionals. Security and privacy for patients' medical data are crucial for the acceptance and ubiquitous use of IoT in healthcare. The main focus of this work is to secure Authentication and Authorization of all the devices, Identifying and Tracking the devices deployed in the system, Locating and tracking of mobile devices, new things deployment and connection to existing system, Communication among the devices and data transfer between remote healthcare systems. The proposed system uses asynchronous communication between the applications and data servers deployed in the cloud environment.

Achieving Cloud Security Using a Third Party Auditor and Preserving Privacy for Shared Data Over a Public Cloud

2021 ◽  
pp. 1371-1391
Author(s):  
Vitthal Sadashiv Gutte ◽  
Sita Devulapalli
Keyword(s):  
Cloud Security ◽  
Third Party ◽  
Security Model ◽  
Cloud Environment ◽  
Public Cloud ◽  
Shared Data ◽  
Metadata File ◽  
Efficient Mechanisms ◽  
Different Levels ◽  
Access Security

Correctness of data and efficient mechanisms for data security, while transferring the file to and from Cloud, are of paramount importance in today's cloud-centric processing. A mechanism for correctness and efficient transfer of data is proposed in this article. While processing users request data, a set of attributes are defined and checked. States with attributes at different levels are defined to prevent unauthorized access. Security is provided while storing the data using a chunk generation algorithm and verification of chunks using lightweight Third-Party Auditor (TPA). TPA uses digital signatures to verify user's data that are generated by RSA with MD5 algorithms. The metadata file of generated chunks is encrypted using a modified AES algorithm. The proposed method prevents unauthorized users from accessing the data in the cloud environment, in addition to maintaining data integrity. Results of the proposed cloud security model implementation are discussed.

An Affordable Hybrid Cloud Based Cluster for Secure Health Informatics Research

2018 ◽  
Vol 8 (2) ◽  
pp. 27-46
Author(s):  
Basit Qureshi
Keyword(s):  
Data Storage ◽  
Health Informatics ◽  
Low Cost ◽  
Academic Research ◽  
Security And Privacy ◽  
Hybrid Cloud ◽  
Public Cloud ◽  
Public And Private ◽  
Attribute Based Encryption ◽  
Patient Health

This article describes how a major risk factor in the deployment of patient health records systems in the cloud is the security and privacy of data. Hybrid cloud solutions have been proposed that leverage the public and private cloud deployment to manage and alleviate accessibility, access control and privacy concerns. This article presents a privacy preserving and secure architecture for data acquisition, storage, processing and sharing. The proposed architecture is composed of a public cloud-based services that interact with a low-cost cloud computing cluster (LoC4) as a backend. A lightweight data security eco-system based on attribute based encryption is developed to provide security for public cloud-based data storage. Performance of the deployment is evaluated in a real-time deployment environment. The results show that the proposed ABE-based system is 2.3 times faster than AES-based for a variety of sizes of data blocks. It is further noted that the low-cost and affordability of LoC4 platform offers excellent opportunities for academic research in cloud based health informatics.

Migration of applications to the Cloud: a user-driven approach

2016 ◽  
Vol 2 (1) ◽  
Author(s):  
Anastasia Panori ◽  
Agustín González-Quel ◽  
Miguel Tavares ◽  
Dimitris Simitopoulos ◽  
Julián Arroyo
Keyword(s):  
Cloud Computing ◽  
Smart City ◽  
Public Services ◽  
Cloud Services ◽  
Cloud Environment ◽  
Public Cloud ◽  
Cloud Infrastructure ◽  
Migration Process ◽  
Empirical Application ◽  
Selection Of

During the last decade, there has been an increased interest on cloud computing and especially on the adoption of public cloud services. The process of developing cloud-based public services or migrating existing ones to the Cloud is considered to be of particular interest—as it may require the selection of the most suitable applications as well as their transformation to fit in the new cloud environment. This paper aims at presenting the main findings of a migration process regarding smart city applications to a cloud infrastructure. First, it summarises the methodology along with the main steps followed by the cities of Agueda (Portugal), Thessaloniki (Greece) and Valladolid (Spain) in order to implement this migration process within the framework of the STORM CLOUDS project. Furthermore, it illustrates some crucial results regarding monitoring and validation aspects during the empirical application that was conducted via these pilots. These findings should be received as a helpful experience for future efforts designed by cities or other organisations that are willing to move their applications to the Cloud.

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