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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
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Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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2018-Jun-27
Clarivate Analytics published the InCites Journal Citations Report for 2017. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.699, and the JCR 5-Year Impact Factor is 0.674.

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With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

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  2/2012 - 1
View TOC | « Previous Article | Next Article »

Performance Analysis of Cell-Phone Worm Spreading in Cellular Networks through Opportunistic Communications

YAHUI, W. See more information about YAHUI, W. on SCOPUS See more information about YAHUI, W. on IEEExplore See more information about YAHUI, W. on Web of Science, DENG, S. See more information about  DENG, S. on SCOPUS See more information about  DENG, S. on SCOPUS See more information about DENG, S. on Web of Science, HUANG, H. See more information about  HUANG, H. on SCOPUS See more information about  HUANG, H. on SCOPUS See more information about HUANG, H. on Web of Science, DENG, Y. See more information about DENG, Y. on SCOPUS See more information about DENG, Y. on SCOPUS See more information about DENG, Y. on Web of Science
 
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (720 KB) | Citation | Downloads: 880 | Views: 2,937

Author keywords
opportunistic communications, delay tolerant network, 3G networks, Markov process, cell-phone worms

References keywords
mobile(14), networks(10), malware(10), sarkar(5), khouzani(5), infocom(5), infcom(5), worm(4), network(4), delay(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2012-05-30
Volume 12, Issue 2, Year 2012, On page(s): 3 - 8
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2012.02001
Web of Science Accession Number: 000305608000001
SCOPUS ID: 84865306374

Abstract
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Worms spreading directly between cell-phones over short-range radio (Bluetooth, WiFi, etc.) are increasing rapidly. Communication by these technologies is opportunistic and has very close relation with the social characteristics of the phone carriers. In this paper, we try to evaluate the impact of different characteristics on the spreading performance of worms. On the other hand, the behaviors of worms may have certain impact, too. For example, worms may make phones be completely dysfunctional and these phones can be seen as killed. We study the impact of the killing speed. Using the Markov model, we propose some theoretical models to evaluate the spreading performance in different cases. Simulation results show the accuracy of our models. Numerical results show that if users do not believe the data coming from others easily, the worms may bring less damage. Surprisingly, if the users are more willing to install the anti-virus software, the worms may bring bigger damage when the software becomes to be outdated with high probability. Though the worms can bring big damage on the network temporarily by killing phones rapidly, numerical results show that this behavior may decrease the total damage in the long time. Therefore, killing nodes more rapidly may be not optimal for worms.


References | Cited By  «-- Click to see who has cited this paper

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[CrossRef] [Web of Science Times Cited 34] [SCOPUS Times Cited 78]


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[CrossRef] [SCOPUS Times Cited 40]


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[CrossRef]


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[CrossRef] [Full Text] [Web of Science Times Cited 5] [SCOPUS Times Cited 5]


[7] T. Spyropoulos, T. Turletti, and K. Obrazcka, "Routing in delay tolerant networks comprising heterogeneous populations of nodes," IEEE Trans. Mobile Computing, vol.8, no. 8, Aug. 2009.
[CrossRef] [Web of Science Times Cited 97] [SCOPUS Times Cited 130]


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[CrossRef] [Web of Science Times Cited 46] [SCOPUS Times Cited 72]


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[CrossRef] [SCOPUS Times Cited 14]


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[CrossRef] [SCOPUS Times Cited 137]


[18] MHR. Khouzani, E. Altman, and S. Sarkar, "Optimal quarantining of wireless malware through power control," in Proc. Fourth Symposium on Information Theory and Applications, University of California, San Diego, Feb. 2009.
[CrossRef]


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[CrossRef] [SCOPUS Times Cited 31]


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[CrossRef] [Web of Science Times Cited 13] [SCOPUS Times Cited 22]


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References Weight

Web of Science® Citations for all references: 600 TCR
SCOPUS® Citations for all references: 3,439 TCR

Web of Science® Average Citations per reference: 22 ACR
SCOPUS® Average Citations per reference: 127 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2018-10-18 02:15 in 177 seconds.




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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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