alexa Privacy-Assured OIRS Service with Performance Speedup
ISSN ONLINE(2320-9801) PRINT (2320-9798)

International Journal of Innovative Research in Computer and Communication Engineering
Open Access

OMICS International organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific Societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

Open Access Journals gaining more Readers and Citations

700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ Readers

This Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)

Special Issue Article

Privacy-Assured OIRS Service with Performance Speedup in Cloud

P.ARUNPRIYA1,S.RINESH2
  1. ME, Dept. of CSE, Karpagam University, Coimbatore, Tamil Nadu, India
  2. Assistant Professor, Dept. of CSE, Karpagam University, Coimbatore, Tamil Nadu, India
Related article at Pubmed, Scholar Google
 

Abstract

At the moment wide Ranging image data sets are being rapidly generated. Along with such data explosion is the fast-growing vogue to outsource the image management systems to the cloud for its lavish computing resources and benefits.However,how to protect the sensitive data while enabling outsourced image services, becomes a major concern. To address these challenges, we propose outsourced image recovery service (OIRS), a novel outsourced image recovery service architecture, which deeds different domain technologies and takes security, efficiency, and design complexity into consideration from the very beginning of the service flow. Specifically, we choose to design OIRS under the compressed sensing framework, which is known for its simplicity of unifying the traditional sampling and compression for image attainment. Data owners only need to outsource compressed image samples to cloud for diminish storage overhead. In addition, in OIRS, data users can hitch the cloud to securely reconstruct images without enlightening information from either the compressed image samples or the underlying image content. We start with the OIRS design for sparse data, which is the typical application scenario for compressed sensing, and then show its natural extension to the general data for meaningful tradeoffs between efficiency and accuracy. We thoroughly analyze the privacy-protection of OIRS and conduct far reaching experiments to demonstrate the system effectiveness and efficiency. For completeness, we also discuss the expected performance speedup of OIRS through hardware built-in system design.

Keywords

Share This Page

Additional Info

Loading
Loading Please wait..
Peer Reviewed Journals
 
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals
International Conferences 2017-18
 
Meet Inspiring Speakers and Experts at our 3000+ Global Annual Meetings

Contact Us

 
© 2008-2017 OMICS International - Open Access Publisher. Best viewed in Mozilla Firefox | Google Chrome | Above IE 7.0 version
adwords