Next Article in Journal
A (1 + 2)-Dimensional Simplified Keller–Segel Model: Lie Symmetry and Exact Solutions. II
Next Article in Special Issue
Detecting Sybil Attacks in Cloud Computing  Environments Based on Fail‐Stop Signature
Previous Article in Journal
Comparing Lifetimes of Series and Parallel Systems with Heterogeneous Fréchet Components
Previous Article in Special Issue
Improved Asymmetric Cipher Based on Matrix Power Function with Provable Security
Open AccessArticle

Data-Filtering System to Avoid Total Data Distortion in IoT Networking

1
Department of Software Engineering, Changshin University, Changwon 51352, Korea
2
Department of Multimedia Engineering, Dongguk University, Seoul 04620, Korea
3
Department of Computer Software Engineering, Soonchunhyang University, Asan 31538, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Young-Sik Jeong
Symmetry 2017, 9(1), 16; https://doi.org/10.3390/sym9010016
Received: 30 September 2016 / Revised: 25 December 2016 / Accepted: 16 January 2017 / Published: 20 January 2017
(This article belongs to the Special Issue Symmetry in Secure Cyber World)
In the Internet of Things (IoT) networking, numerous objects are connected to a network. They sense events and deliver the sensed information to the cloud. A lot of data is generated in the IoT network, and servers in the cloud gather the sensed data from the objects. Then, the servers analyze the collected data and provide proper intelligent services to users through the results of the analysis. When the server analyzes the collected data, if there exists malfunctioning data, distortional results of the analysis will be generated. The distortional results lead to misdirection of the intelligent services, leading to poor user experience. In the analysis for intelligent services in IoT, malfunctioning data should be avoided because integrity of the collected data is crucial. Therefore, this paper proposes a data-filtering system for the server in the cloud. The proposed data-filtering system is placed in front of the server and firstly receives the sensed data from the objects. It employs the naïve Bayesian classifier and, by learning, classifies the malfunctioning data from among the collected data. Data with integrity is delivered to the server for analysis. Because the proposed system filters the malfunctioning data, the server can obtain accurate analysis results and reduce computing load. The performance of the proposed data-filtering system is evaluated through computer simulation. Through the simulation results, the efficiency of the proposed data-filtering system is shown. View Full-Text
Keywords: data-filtering system; data distortion; naïve Bayesian classifier; Internet of Things (IoT) data-filtering system; data distortion; naïve Bayesian classifier; Internet of Things (IoT)
Show Figures

Graphical abstract

MDPI and ACS Style

Kim, D.-Y.; Jeong, Y.-S.; Kim, S. Data-Filtering System to Avoid Total Data Distortion in IoT Networking. Symmetry 2017, 9, 16.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop