Big Data Security in the Web-Based Cloud Storage System Using 3D-AES Block Cipher Cryptography Algorithm

Author(s):  
Nur Afifah Nadzirah Adnan ◽  
Suriyani Ariffin
2020 ◽  
Vol 1486 ◽  
pp. 052014
Author(s):  
Jianbao Zhu ◽  
Jing Fu ◽  
Yuwei Sun ◽  
Ye Shi ◽  
Yu Chen ◽  
...  

2020 ◽  
Vol 48 (W1) ◽  
pp. W403-W414
Author(s):  
Fabrice P A David ◽  
Maria Litovchenko ◽  
Bart Deplancke ◽  
Vincent Gardeux

Abstract Single-cell omics enables researchers to dissect biological systems at a resolution that was unthinkable just 10 years ago. However, this analytical revolution also triggered new demands in ‘big data’ management, forcing researchers to stay up to speed with increasingly complex analytical processes and rapidly evolving methods. To render these processes and approaches more accessible, we developed the web-based, collaborative portal ASAP (Automated Single-cell Analysis Portal). Our primary goal is thereby to democratize single-cell omics data analyses (scRNA-seq and more recently scATAC-seq). By taking advantage of a Docker system to enhance reproducibility, and novel bioinformatics approaches that were recently developed for improving scalability, ASAP meets challenging requirements set by recent cell atlasing efforts such as the Human (HCA) and Fly (FCA) Cell Atlas Projects. Specifically, ASAP can now handle datasets containing millions of cells, integrating intuitive tools that allow researchers to collaborate on the same project synchronously. ASAP tools are versioned, and researchers can create unique access IDs for storing complete analyses that can be reproduced or completed by others. Finally, ASAP does not require any installation and provides a full and modular single-cell RNA-seq analysis pipeline. ASAP is freely available at https://asap.epfl.ch.


2018 ◽  
Vol 7 (3.6) ◽  
pp. 55
Author(s):  
Neha Narayan Kulkarni ◽  
Shital Kumar A. Jain ◽  
. .

Recently the technologies are growing fast, so they have become the point of source and also the sink for data. Data is generated in large volume introducing the concept of structured and unstructured data evolving "Big Data" which needs large memory for storage. There are two possible solutions either increase the local storage or use the Cloud Storage. Cloud makes data available to the user anytime, anywhere, anything. Cloud allows the user to store their data virtually without investing much. However, this data is on cloud raising a concern of data security and recovery. This attack is made by the untrusted or unauthorized user remotely. The attacker may modify, delete or replace the data. Therefore, different models are proposed for a data integrity check and proof of retrievability. This paper includes the literature review related to various techniques for data integrity, data recovery and proof of retrievability.  


2013 ◽  
Vol 834-836 ◽  
pp. 1795-1798
Author(s):  
Jun Qin ◽  
Ya Ping Zhang ◽  
Ping Zong

In cloud computing applications, the data security is a primary concern of user. In this paper, for the problem that data of the HDFS cannot be destroyed completely in open source cloud storage system, which may lead to data leakage, it designs a destruction mechanism of HDFS with multiple security level. This mechanism make data effectively destroyed by the method of data overwrite which makes a balance between security requirements and performance requirements. The Simulation experiments show that the mechanism can override a Block file in HDFS environment effectively to achieve the purpose of data destroying. At the same the overhead of different overwrite algorithm is different also which can ensure the security and efficiency is balanced.


2020 ◽  
Vol 17 (9) ◽  
pp. 3979-3982
Author(s):  
N. Harish Kumar ◽  
G. Deepak

Internet of Things has been increasing its usage and recognition in vast sectors like Defence, Business, Industries, and Hospitals. The data disruption is strictly unacceptable in a number of these sectors because it could end up in serious Loss or Damages to the entire system. As of now, IOT is using a central cloud storage system for information storage and transactions. However, some examples already verified that Central cloud storage information might be hacked and changed by the specialists. This paper presents an IoT system having localized block chain storage which works on real time data and manipulates with narrowness of data interruption and modification and its recovery.


In the cryptocurrency era, Blockchain is one of the expeditiously growing information technologies that help in providing security to the data. Data tampering and authentication problems generally occur in centralized servers while sharing and storing the data. Blockchain provides the platform for big data and cloud storage in enhancing the security by evading from pernicious users. In this paper, we have discussed the exhaustive description of blockchain and its need, features and applications. Analysis of blockchain is done for different domains such as big data, cloud, internet of things and mobile cloud where the differences V’s are compared with big data and blockchain. SWOT (Strength Weakness Opportunities Threats) analysis is performed to address the merits and limitations in blockchain technology. The survey in aspects of data security, data storage, data sharing and data authentication through blockchain technology is done and the challenges are discussed to overcome the problem that leads in big data and cloud storage. The detailed comparative analysis proves that the blockchain technology overcomes the problems in big data storage and data security in cloud.


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