Indicadores para la detección de ataques ransomware

The growing number of devices sharing personal information and the privacy provided by cryptocurrencies have motivated the development of new attack vectors. [...]a proof- of-concept of an automatic learning model based on the filtered information is presented. Agradecimientos: La presente investiga...

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Bibliographic Details
Published in:RISTI : Revista Ibérica de Sistemas e Tecnologias de Informação 2019-04 (E19), p.493-506
Main Authors: Veloz, Freddy Daniel Bazante, López, Lorena Isabel Barona, Caraguay, Ángel Leonardo Valdivieso, Álvarez, Myriam Beatriz Hernández
Format: Article
Language:Spanish
Subjects:
Artificial intelligence
Automation
Communications traffic
Computer viruses
Digital currencies
Intelligence gathering
International conferences
Machine learning
Malware
Ransomware
Threat evaluation
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Summary:The growing number of devices sharing personal information and the privacy provided by cryptocurrencies have motivated the development of new attack vectors. [...]a proof- of-concept of an automatic learning model based on the filtered information is presented. Agradecimientos: La presente investigación es financiada por la Escuela Politécnica Nacional, dentro del proyecto interno Ransomware a gran escala por medio de Seguridad Cognitiva (2018), número PII-17-14. 1 Cuckoo Sandbox Book v2.0.6. https://cuckoo.sh/docs/ 2 RapidMiner. https://rapidminer.com/resource/state-deep-learning/ 3 Virus Total Free Online Virus, Malware and URL Scanner. https://www.virustotal.com/es/ 4 Talos Group - Comprehensive Threat Intelligence. https://www.talosintelligence.com/ Referencias Alam, M., Bhattacharya, S., Mukhopadhyay, D., & Chattopadhyay, A. (2018). Leveraging Machine Learning Techniques for Windows Ransomware Network Traffic Detection.
ISSN:1646-9895