Cargando…
Cognitive Models in Cybersecurity: Learning From Expert Analysts and Predicting Attacker Behavior
Cybersecurity stands to benefit greatly from models able to generate predictions of attacker and defender behavior. On the defender side, there is promising research suggesting that Symbolic Deep Learning (SDL) may be employed to automatically construct cognitive models of expert behavior based on s...
Autores principales: | Veksler, Vladislav D., Buchler, Norbou, LaFleur, Claire G., Yu, Michael S., Lebiere, Christian, Gonzalez, Cleotilde |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7308471/ https://www.ncbi.nlm.nih.gov/pubmed/32612551 http://dx.doi.org/10.3389/fpsyg.2020.01049 |
Ejemplares similares
-
Simulations in Cyber-Security: A Review of Cognitive Modeling of Network Attackers, Defenders, and Users
por: Veksler, Vladislav D., et al.
Publicado: (2018) -
Mission Command in the Age of Network-Enabled Operations: Social Network Analysis of Information Sharing and Situation Awareness
por: Buchler, Norbou, et al.
Publicado: (2016) -
Creative Persuasion: A Study on Adversarial Behaviors and Strategies in Phishing Attacks
por: Rajivan, Prashanth, et al.
Publicado: (2018) -
Editorial: Cognition, Behavior and Cybersecurity
por: Watters, Paul, et al.
Publicado: (2021) -
Security under Uncertainty: Adaptive Attackers Are More Challenging to Human Defenders than Random Attackers
por: Moisan, Frédéric, et al.
Publicado: (2017)