Secure data processing with massive-parallel SIMD matrix for embedded SoC in digital-convergence mobile devices

2016 ◽  
Vol 12 (1) ◽  
pp. 96-104 ◽  
Author(s):  
Takeshi Kumaki ◽  
Tetsushi Koide ◽  
Takeshi Fujino
Keyword(s):  
Data Processing ◽  
Mobile Devices ◽  
Digital Convergence ◽  
Secure Data ◽  
Embedded Soc

SDPBDVC: secure data processing on big data using visual cryptography

2020 ◽  
Vol 26 (2/3) ◽  
pp. 237
Author(s):  
K. Brindha ◽  
N. Jeyanthi
Keyword(s):  
Big Data ◽  
Data Processing ◽  
Visual Cryptography ◽  
Secure Data

scholarly journals An efficient and secure data sharing scheme for mobile devices in cloud computing

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Xiuqing Lu ◽  
Zhenkuan Pan ◽  
Hequn Xian
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
Data Sharing ◽  
Data Privacy ◽  
Mobile Terminals ◽  
Sensitive Data ◽  
Integrity Verification ◽  
Sharing Scheme ◽  
Secure Data ◽  
Authorized Access

Abstract With the development of big data and cloud computing, more and more enterprises prefer to store their data in cloud and share the data among their authorized employees efficiently and securely. So far, many different data sharing schemes in different fields have been proposed. However, sharing sensitive data in cloud still faces some challenges such as achieving data privacy and lightweight operations at resource constrained mobile terminals. Furthermore, most data sharing schemes have no integrity verification mechanism, which would result in wrong computation results for users. To solve the problems, we propose an efficient and secure data sharing scheme for mobile devices in cloud computing. Firstly, the scheme guarantees security and authorized access of shared sensitive data. Secondly, the scheme realizes efficient integrity verification before users share the data to avoid incorrect computation. Finally, the scheme achieves lightweight operations of mobile terminals on both data owner and data requester sides.

scholarly journals A Lifelog Browser for Visualization and Search of Mobile Everyday-Life

2014 ◽  
Vol 10 (3) ◽  
pp. 243-258 ◽  
Author(s):  
Keum-Sung Hwang ◽  
Sung-Bae Cho
Keyword(s):  
Bayesian Networks ◽  
Everyday Life ◽  
Mobile Devices ◽  
Mobile Device ◽  
Private Information ◽  
Personal Information ◽  
Mobile Environments ◽  
Digital Convergence ◽  
The Everyday ◽  
Searching Method

Mobile devices can now handle a great deal of information thanks to the convergence of diverse functionalities. Mobile environments have already shown great potential in terms of providing customized service to users because they can record meaningful and private information continually for long periods of time. The research for understanding, searching and summarizing the everyday-life of human has received increasing attention in recent years due to the digital convergence. In this paper, we propose a mobile life browser, which visualizes and searches human's mobile life based on the contents and context of lifelog data. The mobile life browser is for searching the personal information effectively collected on his/her mobile device and for supporting the concept-based searching method by using concept networks and Bayesian networks. In the experiments, we collected the real mobile log data from three users for a month and visualized the mobile lives of the users with the mobile life browser developed. Some tests on searching tasks confirmed that the result using the proposed concept-based searching method is promising.

Secure Data Processing for Industrial Remote Diagnosis and Maintenance

2021 ◽  
pp. 335-346
Author(s):  
Walid Arabi ◽  
Reda Yaich ◽  
Aymen Boudguiga ◽  
Mawloud Omar
Keyword(s):  
Data Processing ◽  
Remote Diagnosis ◽  
Secure Data

Secure Data Processing System Using Decision Tree Architecture

2020 ◽  
pp. 173-180
Author(s):  
T. M. Nived ◽  
Juhi Jyotsna Tiru ◽  
N. Jayapandian ◽  
K. Balachandran
Keyword(s):  
Decision Tree ◽  
Data Processing ◽  
Processing System ◽  
Tree Architecture ◽  
Data Processing System ◽  
Secure Data

ADVANCED TECHNOLOGIES FOR DISTRIBUTED DATABASE SERVICES HYPERINFRASTRUCTURE

2005 ◽  
Vol 20 (16) ◽  
pp. 3877-3879 ◽  
Author(s):  
ALEXANDRE VANIACHINE ◽  
DAVID MALON ◽  
MATTHEW VRANICAR
Keyword(s):  
Data Processing ◽  
Data Access ◽  
Distributed Database ◽  
Lessons Learned ◽  
Heterogeneous Databases ◽  
Event Data ◽  
Production Environment ◽  
Database Access ◽  
Access Methods ◽  
Secure Data

HEP collaborations are deploying grid technologies to address petabyte-scale data processing challenges. In addition to file-based event data, HEP data processing requires access to terabytes of non-event data (detector conditions, calibrations, etc.) stored in relational databases. Inadequate for non-event data delivery in these amounts, database access control technologies for grid computing are limited to encrypted message transfers. To overcome these database access limitations one must go beyond the existing grid infrastructure. A proposed hyperinfrastructure of distributed database services implements efficient secure data access methods. We introduce several technologies laying a foundation of a new hyperinfrastructure. We present efficient secure data transfer methods and secure grid query engine technologies federating heterogeneous databases. Lessons learned in a production environment of ATLAS Data Challenges are presented.

scholarly journals Geo, audio, video, photo: how digital convergence in mobile devices facilitates participatory culture in libraries

2014 ◽  
Vol 64 (1) ◽  
pp. 11-22 ◽  
Author(s):  
Peta Hopkins ◽  
Jo Hare ◽  
Jessie Donaghey ◽  
Wendy Abbott
Keyword(s):  
Mobile Devices ◽  
Participatory Culture ◽  
Digital Convergence ◽  
Audio Video
Sign in / Sign up

Export Citation Format

Share Document