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CFP: IEEE MASS' 2018 Workshop on  Trust, Security and Privacy for Big Data (BigTrust 2018)
 
Venue & Dates: 
Chengdu, China, October 9-12, 2018
Conference Website:
http://res.hnu.edu.cn/hbs/Bigtrust2018/

Introduction
Big Data has the potential for enabling new insights to change science, engineering, medicine, healthcare, finance, 
business, and ultimately society itself. Current work on Big Data focuses on information processing such as data 
mining and analysis. However, trust, security and privacy of Big Data are vital concerns that have received less 
research focus. Regarding the above context, this workshop proposal is aimed at bringing together people from both 
academia and industry to present their most recent work related to trust, security and privacy issues in Big Data, 
and exchange ideas and thoughts in order to identify emerging research topics and define the future of Big Data.
BigTrust 2018 is a part of MASS 2018, the 15th IEEE International Conference on Mobile Ad-hoc and Sensor Systems.  
The scope and interests for the special issue include but are not limited to the following list:

Big Data Science, Foundations, and applications
           Novel Theoretical Models for Big Data.
           New Computational Models for Big Data.
           Data and Information Quality for Big Data.
           High Performance/Parallel Computing Platforms for Big Data .
           Energy-efficient Computing for Big Data.
           Big Data Search Architectures, Scalability and Efficiency.
           Visualization Analytics for Big Data.
           Data Acquisition, Integration, Cleaning, and Best Practices .
 
Trust in Big Data
           Trust semantics, metrics, and models for Big Data.
           Trust management and evaluation for Big Data.
           Trusted systems, software, and applications for Big Data.
           Trusted platform implementation technologies for Big Data.
           Information quality/trustworthiness for Big Data.
           Provenance of content for Big Data.
           Trustworthiness of ratings/recommender systems for Big Data.
 
Security & Privacy in Big Data
           Security model and architecture for Big Data.
           Software and system security for Big Data.
           Cryptography in Big Data.
           Big Data privacy policies and standards.
           Anonymization techniques for big data.
           Security and Privacy in Big Data sharing and visualization.
           Security and Privacy in Big Data access control mechanisms.
           Security and Privacy in Big Data mining and analytics
 
Submission and Publication Information
All BigTrust 2018 presented papers will b published in the conference proceedings and submitted to IEEE Xplore. 
Submitted papers should be written in the English language, with a maximum page limit of 6 printed pages, including 
all the figures, references and appendices, and not published or under review elsewhere. Papers longer than 6 pages 
will not be reviewed. 

Use the standard IEEE Conference templates for Microsoft Word or LaTeX formats found at:  
https://www.ieee.org/conferences/publishing/templates.html. Please submit your paper at 
https://easychair.org/conferences/?conf=BigTrust2018.
 
Important Dates
(1)  Paper Submission Deadline:         July 30, 2018  
(2)  Author Notification:                         August 15, 2018
(3)  Camera-ready Papers Due:           September  15, 2018
(4)  Conference Dates:                         October 9th-12th, 2018
 

 
General Co-Chairs
Qin Liu && Wenjun Jiang, Hunan University, China
MD Zakirul Alam,  Fordham University, USA
Ling You, National Key Laboratory of Science and Technology on Blind Signal Processing, China 
Mingjun Xiao, University of Science and Technology of China, China
 
Please email inquiries concerning BigTrust 2018 to:
Qin Liu: [log in to unmask]; [log in to unmask]




--
Dr. Qin Liu
College of Computer Science and Electronic Engineering
Hunan University
Changsha, Hunan Province,P.R. China, 410082
Mobile: +86-13548577157
Email: [log in to unmask]; [log in to unmask]
Homepage: http://res.hnu.edu.cn/hbs/lq/


 



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