Document Type
Article
Publication Date
2019
DOI
10.4108/eai.13-7-2018.162808
Publication Title
EAI Endorsed Transactions on Security and Safety
Volume
6
Issue
21
Pages
e2 (1-18)
Abstract
In modern days, cyber networks need continuous monitoring to keep the network secure and available to legitimate users. Cyber attackers use reconnaissance mission to collect critical network information and using that information, they make an advanced level cyber-attack plan. To thwart the reconnaissance mission and counterattack plan, the cyber defender needs to come up with a state-of-the-art cyber defense strategy. In this paper, we model a dynamic deception system (DDS) which will not only thwart reconnaissance mission but also steer the attacker towards fake network to achieve a fake goal state. In our model, we also capture the attacker’s capability using a belief matrix which is a joint probability distribution over the security states and attacker types. Experiments conducted on the prototype implementation of our DDS confirm that the defender can make the decision whether to spend more resources or save resources based on attacker types and thwart reconnaissance mission.
Rights
Copyright © 2019 EAI Endorsed Transactions on Security and Safety
This is an open-access article distributed under the terms Creative Commons Attribution 3.0 Unported (CC BY 3.0) License, which permits unlimited use, distribution, and reproduction in any medium so long as the original work is properly cited.
Original Publication Citation
Al Amin, M. A. R., Shetty, S., Njilla, L., Tosh, D., & Kamhoua, C. (2019). Attacker capability based dynamic deception model for large-scale networks. EAI Endorsed Transactions on Security and Safety, 6(21), Article e2. https://doi.org/10.4108/eai.13-7-2018.162808
ORCID
0000-0002-2459-171X (Al Amin), 0000-0002-8789-0610 (Shetty)
Repository Citation
Al Amin, Md Ali Reza; Shetty, Sachhin; Njilla, Laurent; Tosh, Deepak K.; and Kamhoua, Charles, "Attacker Capability Based Dynamic Deception Model for Large-Scale Networks" (2019). Computational Modeling & Simulation Engineering Faculty Publications. 74.
https://digitalcommons.odu.edu/msve_fac_pubs/74