Detection of Mobile Botnets using Neural Networks
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F16%3A43875606" target="_blank" >RIV/70883521:28140/16:43875606 - isvavai.cz</a>
Result on the web
<a href="http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7821774" target="_blank" >http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7821774</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/FTC.2016.7821774" target="_blank" >10.1109/FTC.2016.7821774</a>
Alternative languages
Result language
angličtina
Original language name
Detection of Mobile Botnets using Neural Networks
Original language description
This poster deals with botnets, the most dangerous kind of mobile malware, and their detection using neural networks. Unlike common mobile malware, botnets often have a complicated pattern of behavior because they are not managed by predictable algorithms but they are controlled by humans via command and control servers (C&C servers) or via peer-to-peer networks. However, they have certain common features which have been revealed by analysis of contemporary mobile botnets. These features have been used for creation of a neural network training set. Finally, the design of parallel architecture using neural network for useful detection of mobile botnets has been described.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 2016 Future Technologies Conference (FTC)
ISBN
978-1-5090-4171-8
ISSN
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e-ISSN
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Number of pages
3
Pages from-to
1324-1326
Publisher name
IEEE
Place of publication
New Jersey, Piscataway
Event location
San Francisco
Event date
Dec 6, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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