Title
A Novel Architecture for Automatic Document Classification for Effective Security in Edge Computing Environments
Abstract
Existing automatic document classification architectures are underpinned by the transfer of raw document data streams to the cloud computing environment for processing and analysis. This operation is expensive, has limitation to meet the real-time processing needs, and exposes potential security and privacy risks at the data transfer process. In this paper, we present a novel architecture for document classification with enhanced security that incorporates mechanism to facilitate the processing and analysis of raw data streams near the source of the data.
Year
DOI
Venue
2018
10.1109/SEC.2018.00056
2018 IEEE/ACM Symposium on Edge Computing (SEC)
Keywords
Field
DocType
Edge Computing, Big Data, Confidentiality, Security, Machine Learning
Edge computing,Document classification,Data stream mining,Architecture,Data transmission,Computer science,Computer security,Raw data,Big data,Database,Cloud computing
Conference
ISBN
Citations 
PageRank 
978-1-5386-9446-6
1
0.35
References 
Authors
14
2
Name
Order
Citations
PageRank
Lei Ding114226.77
Malek Ben Salem218516.19