A Secured Data Processing Technique for Effective Utilization of Cloud Computing

Abstract

International audience Digital humanities require IT Infrastructure and sophisticated analytical tools, including datavisualization, data mining, statistics, text mining and information retrieval. Regarding funding, tobuild a local data center will necessitate substantial investments. Fortunately, there is another optionthat will help researchers take advantage of these IT services to access, use and share informationeasily. Cloud services ideally offer on-demand software and resources over the Internet to read andanalyze ancient documents. More interestingly, billing system is completely flexible and based onresource usage and Quality of Service (QoS) level. In spite of its multiple advantages, outsourcingcomputations to an external provider arises several challenges. Specifically, security is the majorfactor hindering the widespread acceptance of this new concept. As a case study, we review the use ofcloud computing to process digital images safely. Recently, various solutions have been suggested tosecure data processing in cloud environement. Though, ensuring privacy and high performance needsmore improvements to protect the organization's most sensitive data. To this end, we propose aframework based on segmentation and watermarking techniques to ensure data privacy. In this respect,segementation algorithm is used to to protect client's data against untauhorized access, whilewatermarking method determines and maintains ownership. Consequentely, this framework willincrease the speed of development on ready-to-use digital humanities tools.

A Smart Factory Architecture Based on Industry 4.0 Technologies: Open-Source Software Implementation

“…In comparison, the Cloud executes the Machine Learning for data classification, using relevant information received from the Edge (HTTPS) or the CPS (MQTT); once the model returns the prediction, the result is sent, as feedback, to the DA element for visualization and reporting. Computing as a model for enabling on-demand network access to a shared pool of configurable computing resources (networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction [79]. According to Birje et al, the four deployment models include public, private, hybrid, and community cloud.…”

Quantum Attack-Resistant Security System for Cloud Computing using Lattice Cryptography

“…This can be linked to the benefits of cloud computing, which cloud providers present to cloud consumers. These benefits include scalability, elasticity, powerful calculations, and lower service costs, despite the fact that data security is one of the roadblocks to mainstream use of cloud services [1]. Reference [3], defines data security as "a method of protecting digital data, such as data stored in a database, from attackers and unauthorised actions of unauthorized users.…”