scholarly journals Optimal Network Coding-Based In-Network Data Storage and Data Retrieval for IoT/WSNs

2015 ◽  
Author(s):  
Camila H.S. Oliveira ◽  
Yacine Ghamri-Doudane ◽  
Carlos Eduardo F. Brito ◽  
Stephane Lohier
Keyword(s):  
Network Coding ◽  
Data Storage ◽  
Data Retrieval ◽  
Network Data ◽  
Optimal Network

scholarly journals Study of privacy-preserving framework for cloud storage

2011 ◽  
Vol 8 (3) ◽  
pp. 801-819 ◽  
Author(s):  
Huang Ruwei ◽  
Gui Xiaolin ◽  
Yu Si ◽  
Zhuang Wei
Keyword(s):  
Data Storage ◽  
Cloud Storage ◽  
Security Analysis ◽  
Bloom Filter ◽  
Data Access ◽  
Data Retrieval ◽  
Privacy Preserving ◽  
Index Structure ◽  
Structure Generation ◽  
Access Right

In order to implement privacy-preserving, efficient and secure data storage and access environment of cloud storage, the following problems must be considered: data index structure, generation and management of keys, data retrieval, treatments of change of users? access right and dynamic operations on data, and interactions among participants. To solve those problems, the interactive protocol among participants is introduced, an extirpation-based key derivation algorithm (EKDA) is designed to manage the keys, a double hashed and weighted Bloom Filter (DWBF) is proposed to retrieve the encrypted keywords, which are combined with lazy revocation, multi-tree structure, asymmetric and symmetric encryptions, which form a privacypreserving, efficient and secure framework for cloud storage. The experiment and security analysis show that EKDA can reduce the communication and storage overheads efficiently, DWBF supports ciphertext retrieval and can reduce communication, storage and computation overhead as well, and the proposed framework is privacy preserving while supporting data access efficiently.

scholarly journals RANCANG BAGUN SISTEM INFORMASI AGENDA KERJA UNTUK ANGGOTA KEPOLISIAN BERBASIS KINERJA MENGGUNAKAN METODE BERORIENTASI OBJEK

2021 ◽  
Vol 14 (2) ◽  
pp. 181-189
Author(s):  
Edy Siswanto ◽  
Sugiarto Sugiarto
Keyword(s):  
Data Processing ◽  
Data Storage ◽  
Data Retrieval ◽  
Integrated System ◽  
The Body ◽  
Police Chief ◽  
Activity Data ◽  
Public Servant ◽  
The Law ◽  
The Republic

Within the body of the National Police, the Polsekta / Polsek have an important role in protecting, nurturing, serving and enforcing the law in the Tegowanu Police area community. Therefore, the Tegowanu Police are required to be able to serve the community where one of the main tasks of the Republic of Indonesia Police is as a public servant. As one of the law enforcement officers, the National The old work agenda system still uses manual methods and takes a lot of time and with this system will slow down the performance of Polsek members. Documentation of activities carried out by the Tegowanu Police Officer cannot be seen by the police chief and members, because photo documentation is only stored on the officer's computer. Another problem is that there is no data storage for community activity data and activity schedules, because there is no storage in the database so that data processing has not been well integrated. By designing a Performance-based Activity information system using the Object Oriented Method at the Tegowanu Police, Resort Grobogan is expected to help data processing so that it is more well integrated and the reporting process and data retrieval are faster if data is needed at any time and create an integrated system with the database. The information that will be built can speed up the process of processing and sending information and activities of the Tegowanu Police to the head of the Sector Police. 

Data Storage, Retrieval and Management

2010 ◽  
pp. 111-140
Author(s):  
Valentin Cristea ◽  
Ciprian Dobre ◽  
Corina Stratan ◽  
Florin Pop
Keyword(s):  
Data Storage ◽  
Resource Sharing ◽  
High Performance ◽  
Large Scale ◽  
Workflow Management ◽  
Large Data ◽  
Data Retrieval ◽  
Distributed Data Storage ◽  
Processing Power ◽  
Data Transfers

The latest advances in network and distributedsystem technologies now allow integration of a vast variety of services with almost unlimited processing power, using large amounts of data. Sharing of resources is often viewed as the key goal for distributed systems, and in this context the sharing of stored data appears as the most important aspect of distributed resource sharing. Scientific applications are the first to take advantage of such environments as the requirements of current and future high performance computing experiments are pressing, in terms of even higher volumes of issued data to be stored and managed. While these new environments reveal huge opportunities for large-scale distributed data storage and management, they also raise important technical challenges, which need to be addressed. The ability to support persistent storage of data on behalf of users, the consistent distribution of up-to-date data, the reliable replication of fast changing datasets or the efficient management of large data transfers are just some of these new challenges. In this chapter we discuss how the existing distributed computing infrastructure is adequate for supporting the required data storage and management functionalities. We highlight the issues raised from storing data over large distributed environments and discuss the recent research efforts dealing with challenges of data retrieval, replication and fast data transfers. Interaction of data management with other data sensitive, emerging technologies as the workflow management is also addressed.

Optimal Elliptic Curve Cryptography-Based Effective Approach for Secure Data Storage in Clouds

2020 ◽  
Vol 11 (4) ◽  
pp. 65-81
Author(s):  
Anju Malik ◽  
Mayank Aggarwal ◽  
Bharti Sharma ◽  
Akansha Singh ◽  
Krishna Kant Singh
Keyword(s):  
Elliptic Curve ◽  
Data Storage ◽  
Elliptic Curve Cryptography ◽  
Search Algorithm ◽  
Distributed Storage ◽  
Data Retrieval ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Sensitive Data ◽  
Cloud Server

With the rapid development of cloud advancement, a data security challenge has emerged. In this paper, a technique based on elliptical cryptography and cuckoo search algorithm is proposed. With this technique, data owners securely store their data files in the cloud server. Initially the user sends a file storage request to store a file in a cloud server provider (CSP). The input file is checked whether it is sensitive or non-sensitive by the user. If the file is sensitive, then it would be split and stored in different virtual machines (VMs), and if the file is non-sensitive, then it would be assigned in a single VM. This approach was used for the first time as per the survey. To add further security, the sensitive data retrieval needs an encryption process that is supported by the proposed algorithm. If the data owner stores the sensitive data to cloud server, the data owner's document is encrypted by the double encryption technique. Here RSA and optimal elliptic curve cryptography (OECC) algorithm is used to encrypt the document with high security. The authors have used cuckoo search algorithm to identify the optimal key in ECC. This paper has proposed a novel cryptography approach for delivering mass distributed storage by which user's original data cannot be directly reached by cloud operators. Hence, this research has proved that the proposed work will give better securable data storage solving the security issues.

scholarly journals Knowledge Base Commons (KBCommons) v1.1: a universal framework for multi-omics data integration and biological discoveries

BMC Genomics ◽  
2019 ◽  
Vol 20 (S11) ◽  
Author(s):  
Shuai Zeng ◽  
Zhen Lyu ◽  
Siva Ratna Kumari Narisetti ◽  
Dong Xu ◽  
Trupti Joshi
Keyword(s):  
Knowledge Base ◽  
Data Storage ◽  
High Performance ◽  
Data Retrieval ◽  
Omics Data ◽  
Web Interface ◽  
Web Resource ◽  
Privilege Management ◽  
Multi Level ◽  
Comprehensive Framework

Abstract Background Knowledge Base Commons (KBCommons) v1.1 is a universal and all-inclusive web-based framework providing generic functionalities for storing, sharing, analyzing, exploring, integrating and visualizing multiple organisms’ genomics and integrative omics data. KBCommons is designed and developed to integrate diverse multi-level omics data and to support biological discoveries for all species via a common platform. Methods KBCommons has four modules including data storage, data processing, data accessing, and web interface for data management and retrieval. It provides a comprehensive framework for new plant-specific, animal-specific, virus-specific, bacteria-specific or human disease-specific knowledge base (KB) creation, for adding new genome versions and additional multi-omics data to existing KBs, and for exploring existing datasets within current KBs. Results KBCommons has an array of tools for data visualization and data analytics such as multiple gene/metabolite search, gene family/Pfam/Panther function annotation search, miRNA/metabolite/trait/SNP search, differential gene expression analysis, and bulk data download capacity. It contains a highly reliable data privilege management system to make users’ data publicly available easily and to share private or pre-publication data with members in their collaborative groups safely and securely. It allows users to conduct data analysis using our in-house developed workflow functionalities that are linked to XSEDE high performance computing resources. Using KBCommons’ intuitive web interface, users can easily retrieve genomic data, multi-omics data and analysis results from workflow according to their requirements and interests. Conclusions KBCommons addresses the needs of many diverse research communities to have a comprehensive multi-level OMICS web resource for data retrieval, sharing, analysis and visualization. KBCommons can be publicly accessed through a dedicated link for all organisms at http://kbcommons.org/.

scholarly journals SOCIAL NETWORK DATA RETRIEVAL USING SEMANTIC TECHNOLOGY

2017 ◽  
Vol 10 (13) ◽  
pp. 31 ◽  
Author(s):  
Abhilash Srivastav ◽  
Alok Chauhan
Keyword(s):  
Social Network ◽  
Semantic Web ◽  
Web Application ◽  
Data Analytics ◽  
Data Retrieval ◽  
Network Data ◽  
Semantic Technology ◽  
Network Applications ◽  
Social Network Data ◽  
Data Mining Algorithms

Social network data analysis is an important problem due to proliferation of social network applications, amount of data these applications generate and potential of insight based on this big data. The objective of present work is to propose architecture for a semantic web application to facilitate meaningful social network data analytics as well as answering query about concerned ontology. Proposed technique links, on one hand, tools based on semantic technology provided by social network applications with data analytics tools and on the other hand extends this link to ontology authoring tools for further inference.   Results obtained from data analytics tool, results of query on generated ontology and benchmarking of the performance of data analytics tool are shown. It has been observed that a semantic web application utilizing above mentioned tools and technologies is more versatile and flexible and further improvements are possible by applying generic data mining algorithms to the above scenario.    

Research of the Construction of Network Data Storage in the New Period

2012 ◽  
Vol 532-533 ◽  
pp. 1248-1252
Author(s):  
Xu Fang
Keyword(s):  
Data Storage ◽  
Network Data ◽  
New Period ◽  
Push Forward ◽  
The New Period

Nowadays the number of the users of the network data storage is becoming more and more. One of the problems we are confronted with is that how to construct our network data storage in the new period. Several typical network data storage is analyzed in the paper and the problems are analyzed .Some advice is put forward about the construction of the network data storage .We hope that the construction of our country’s network data storage can be push forward constantly through our effort.

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