NDLI: Privacy-Preserving Multimedia Big Data Aggregation in Large-Scale Wireless Sensor Networks

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Issue 1s(Special Issue on Smartphone-Based Interactive Technologies, Systems, and Applications and Special Issue on Extended Best Papers from ACM Multimedia 2014), October 2015

Issue 1, August 2015

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) : Volume 11

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) : Volume 10

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) : Volume 9

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) : Volume 8

Privacy-Preserving Multimedia Big Data Aggregation in Large-Scale Wireless Sensor Networks

Content Provider	ACM Digital Library
Author	Wu, Dapeng Yang, Boran Wang, Ruyan Wang, Chonggang Wang, Honggang
Copyright Year	2016
Description	Author Affiliation: Chongqing University of Posts and Telecommunications, University of Massachusetts Dartmouth, Chongqing, China(Interdigital communications, PA, USA (Wang, Chonggang; University of massachusetts dartmouth, University of Electronic Science and Technology of China, North Dartmouth, MA (Wang, Honggang); Wang, Ruyan); Chongqing university of posts and telecommunications, Chongqing, China (Yang, Boran; Wu, Dapeng))
Abstract	To preserve the privacy of multimedia big data and achieve the efficient data aggregation in wireless multimedia sensor networks (WMSNs), a distributed compressed sensing--based privacy-preserving data aggregation (DCSPDA) approach is proposed in this article. First, in this approach, the original multimedia sensor data are compressed and measured by distributed compressed sensing (DCS) and the compressed data measurements are uploaded to the sink, by which the inherent characteristics between sensor data can be obtained. Second, the original multimedia data are jointly recovered and the common and innovation sparse components are obtained through solving the optimization problem and linear equations at the sink. Third, through least squares support vector machine (LSSVM) learning of the sparse components, the sparse position configuration can be determined and disseminated for each node to conduct the privacy-preserving data configuration. After receiving the configuration message, original multimedia sensor data are accordingly customized, compressed, and measured by the common measurement matrix, aggregated at the cluster heads, and transmitted to the sink. Finally, the aggregated multimedia sensor data are recovered by the sink according to the data configuration to achieve the privacy-preserving data aggregation and transmission. Our comparative simulation results validate the efficiency and scalability of DCSPDA and demonstrate that the proposed approach can effectively reduce the communication overheads and provide reliable privacy-preserving with low computational complexity for WMSNs.
Starting Page	1
Ending Page	19
Page Count	19
File Format	PDF
ISSN	15516857
e-ISSN	15516865
DOI	10.1145/2978570
Volume Number	12
Issue Number	4s
Journal	ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-09-15
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Wireless multimedia sensor networks Data aggregation Distributed compressed sensing Privacy-preserving method
Content Type	Text
Resource Type	Article
Subject	Hardware and Architecture Computer Networks and Communications

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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