Sum Aggregation of Time – Series Data with new Preserving System
 |
International Journal of Computer Trends and Technology (IJCTT) | 
|
| © 2015 by IJCTT Journal | ||
| Volume-27 Number-1 |
||
| Year of Publication : 2015 | ||
| Authors : T.Manasa | ||
| DOI : 10.14445/22312803/IJCTT-V27P109 |
T.Manasa "Sum Aggregation of Time – Series Data with new Preserving System". International Journal of Computer Trends and Technology (IJCTT) V27(1):51-57, September 2015. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract -
The usages of mobile devices are
increasing rapidly. Such as a smart mobiles and
having the variety of mobile sensing applications.
Here we may note that the most previous works on
the sensor data aggregation assume a trusted
aggregator and in mobile sensing applications
cannot facilitating the protect user privacy against an
un trusted aggregator. Here they do not consider the
data aggregation. To attain that we derived a new
privacy-preserving protocol. To perform efficient
aggregation the techniques like Homomorphism
encryption and a novel, HMAC based key
management are utilized. We projected two method
to derivating the Min aggregation of the time series
data. In that first can attain accurate Min, another
one attain approximate Min. With this attestable
blunder certification at a great deal of low cost. For
managing the dynamic joins and leaves we are
proposed a scheme. That can exploit the redundancy
in security to decreasing the communication cost for
every join and leaves. The simulation results can
show how much our scheme has much lower
communication overhead then exist.
References
[1] M. Mun, S. Reddy, K. Shilton, N. Yau, J. Burke, D. Estrin,
M.Hansen, E. Howard, R. West, and P. Boda, “Peir, the
PersonalEnvironmental Impact Report, As a Platform for
ParticipatorySensing Systems Research,” Proc. ACM/USENIX
Int’l Conf. MobileSystems, Applications, and Services
(MobiSys ’09), pp. 55-68, 2009
[2] “ Security and High availability in cloud computing
environments” , IBM Global Technology Services June 2011
[3] “Swamp Computing” a.k.a cloud computing
Web security Journal. 2009-12-28.
[4] V. Krishna Reddy, B. thirumal Rao, Dr. L.S.S Reddy, P.Sai
Kiran “Research Issues in Cloud Computing” Global Journal of
Computer Science and Technology volume 11, Issue 11, July
2011.
[5] “Thunder Clouds: Managing SOA-Cloud Risk”,Philip Wik”.
Service Technology Magazine.2011-10-21.
[6] Nidhi Singhal, J.P.S. Raina – Analysis of AES Algorithm for
Better Utilization.
[7] Sherin, Sreedharan, G.Kalpana- Security Issues and
solutions for Cloud Computing.
[8] Jackson Higgins, Kelly (May 19, 2008). "Permanent Denialof-
Service Attack Sabotages Hardware". Dark Reading.
Archived from the original on December 8, 2008.
[9] Ms.S.Kavitha , Ms.P.Aruna Devi , Ms.P.Sudha – Mobile
Computing Denial of Service
[10] V. Rastogi and S. Nath, “Differentially Private Aggregation
ofDistributed Time-Series with Transformation and
Encryption,”Proc. ACM SIGMOD Int’l Conf. Management of
Data, 2010.
Keywords
The simulation results can
show how much our scheme has much lower
communication overhead then exist.