Ransomware File Detection Using Hashes and Machine Learning
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F23%3A00132429" target="_blank" >RIV/00216224:14330/23:00132429 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/10333283" target="_blank" >https://ieeexplore.ieee.org/document/10333283</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICUMT61075.2023.10333283" target="_blank" >10.1109/ICUMT61075.2023.10333283</a>
Alternative languages
Result language
angličtina
Original language name
Ransomware File Detection Using Hashes and Machine Learning
Original language description
This article explores the integration of machine learning hash analysis within a backup system to proactively detect ransomware threats. By combining multiple data sources and employing intelligent algorithms, the proposed system enhances the detection accuracy and mitigates the risk of data loss caused by ransomware attacks. The integration of machine learning techniques enables real-time analysis of cryptographic hash values, facilitating rapid identification and proactive defense against evolving ransomware variants. Through this approach, organizations can bolster their cybersecurity strategies and safe-guard critical data from malicious encryption attempts.
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
20203 - Telecommunications
Result continuities
Project
<a href="/en/project/VK01030030" target="_blank" >VK01030030: Data backup and storage system with integrated active protection against cyber threats</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2023 15th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)
ISBN
9798350393293
ISSN
2157-0221
e-ISSN
2157-023X
Number of pages
4
Pages from-to
107-110
Publisher name
IEEE
Place of publication
Belgium
Event location
Ghent, Belgium
Event date
Jan 1, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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