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@inproceedings{57886,
author = {Husák, Martin and Javorník, Michal},
address = {New York, NY},
booktitle = {2023 IEEE Conference on Communications and Network Security (CNS)},
doi = {http://dx.doi.org/10.1109/CNS59707.2023.10288665},
keywords = {cybersecurity;resilience;lateral movement},
howpublished = {elektronická verze "online"},
language = {eng},
location = {New York, NY},
isbn = {979-8-3503-3945-1},
pages = {1-6},
publisher = {IEEE},
title = {Lightweight Impact Assessment and Projection of Lateral Movement and Malware Infection},
url = {https://ieeexplore.ieee.org/document/10288665},
year = {2023}
}
TY - JOUR
ID - 57886
AU - Husák, Martin - Javorník, Michal
PY - 2023
TI - Lightweight Impact Assessment and Projection of Lateral Movement and Malware Infection
PB - IEEE
CY - New York, NY
SN - 9798350339451
KW - cybersecurity;resilience;lateral movement
UR - https://ieeexplore.ieee.org/document/10288665
N2 - Resilient IT infrastructures must maintain the required service level even when faced with adversarial activity. Not only should we aim at minimizing the attack surface by hardening our cyber assets, but we should also elaborate on how to respond to running cyber attacks and immediate threats in situations where there is not enough time to patch vulnerabilities or other harden the infrastructures. In this work, we propose a lightweight approach to increasing resilience by projecting the attacker's lateral movement or the spread of malware. While related work builds on elaborate vulnerability assessment and analysis of complex attack paths, we were inspired by recent advances in rapid incident response, namely the recommendation of similar devices close to those already exploited. Using this approach, we can provide prompt recommendations using only the easily obtainable data on the cyber assets, such as device fingerprints. We prioritize promptness and applicability over precision, which complements the existing approaches.
ER -
HUSÁK, Martin a Michal JAVORNÍK. Lightweight Impact Assessment and Projection of Lateral Movement and Malware Infection. Online. In \textit{2023 IEEE Conference on Communications and Network Security (CNS)}. New York, NY: IEEE, 2023, s.~1-6. ISBN~979-8-3503-3945-1. Dostupné z: https://dx.doi.org/10.1109/CNS59707.2023.10288665.
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