Malware Detection by Analysing Encrypted Network Traffic with Neural Networks
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F17%3A00317842" target="_blank" >RIV/68407700:21230/17:00317842 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-71246-8_5" target="_blank" >http://dx.doi.org/10.1007/978-3-319-71246-8_5</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-71246-8_5" target="_blank" >10.1007/978-3-319-71246-8_5</a>
Alternative languages
Result language
angličtina
Original language name
Malware Detection by Analysing Encrypted Network Traffic with Neural Networks
Original language description
We study the problem of detecting malware on client computers based on the analysis of HTTPS traffic. Here, malware has to be detected based on the host address, timestamps, and data volume information of the computer’s network traffic. We develop a scalable protocol that allows us to collect network flows of known malicious and benign applications as training data and derive a malware-detection method based on a neural embedding of domain names and a long short-term memory network that processes network flows. We study the method’s ability to detect new malware in a large-scale empirical study.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Machine Learning and Knowledge Discovery in Databases
ISBN
978-3-319-71245-1
ISSN
0302-9743
e-ISSN
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Number of pages
16
Pages from-to
73-88
Publisher name
Springer International Publishing AG
Place of publication
Cham
Event location
Skopje
Event date
Sep 18, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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