Detailed Information on Publication Record

@inproceedings{46288,
   author = {Husák, Martin},
   address = {San Antonio},
   booktitle = {2021 IEEE International Conference on Intelligence and Security Informatics (ISI)},
   doi = {http://dx.doi.org/10.1109/ISI53945.2021.9624774},
   keywords = {ransomware;incident handling;lateral movement;recommender system},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {San Antonio},
   isbn = {978-1-6654-3838-4},
   pages = {1-6},
   publisher = {IEEE},
   title = {Towards a Data-Driven Recommender System for Handling Ransomware and Similar Incidents},
   url = {https://ieeexplore.ieee.org/abstract/document/9624774},
   year = {2021}
}

TY  - JOUR
ID  - 46288
AU  - Husák, Martin
PY  - 2021
TI  - Towards a Data-Driven Recommender System for Handling Ransomware and Similar Incidents
PB  - IEEE
CY  - San Antonio
SN  - 9781665438384
KW  - ransomware;incident handling;lateral movement;recommender system
UR  - https://ieeexplore.ieee.org/abstract/document/9624774
N2  - Effective triage is of utmost importance for cybersecurity incident response, namely in handling ransomware or similar incidents in which the attacker may use self-propagating worms, infected files, or email attachments to spread malware. If a device is infected, it is vital to know which other devices can be infected too or are immediately threatened. The number and heterogeneity of devices in today's network complicate situational awareness of incident handlers, and, thus, we propose a recommender system that uses network monitoring data to prioritize devices in the network based on their similarity and proximity to an already infected device. The system enumerates devices in close proximity in terms of physical and logical network topology and sorts them by their similarity given by the similarity of their behavioral profile, fingerprint, or common history. The incident handlers can use the recommendation to promptly prevent malware from spreading or trace the attacker's lateral movement.
ER  - 

HUSÁK, Martin. Towards a Data-Driven Recommender System for Handling Ransomware and Similar Incidents. Online. In \textit{2021 IEEE International Conference on Intelligence and Security Informatics (ISI)}. San Antonio: IEEE, 2021, p.~1-6. ISBN~978-1-6654-3838-4. Available from: https://dx.doi.org/10.1109/ISI53945.2021.9624774.