When Can the Defender Effectively Deceive Attackers in Security Games?
Authors: Thanh Nguyen, Haifeng Xu9405-9412
AAAI 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We conduct extensive experiments to illustrate our theoretical results in various game settings. Our empirical results align with our theoretical findings, which show that the defender obtains a significant benefit while the attacker suffers a significant loss due to the defender s deception when the attacker plays the Ignorant or Maximin strategies. |
| Researcher Affiliation | Academia | Thanh Nguyen1 and Haifeng Xu2 1Department of Computer and Information Science , University of Oregon, USA 2Department of Computer Science, University of Virginia, USA thanhhng@cs.uoregon.edu, hx4ad@virginia.edu |
| Pseudocode | No | The paper does not contain any pseudocode or clearly labeled algorithm blocks. |
| Open Source Code | No | The paper does not provide any statement or link indicating that the source code for the described methodology is open source or publicly available. |
| Open Datasets | No | The paper states: 'Our experiments use the standard covariance game generator GAMMUT (http: //gamut.stanford/edu), to generate payoff matrices.' It does not use or provide access information for a publicly available or open dataset. |
| Dataset Splits | No | The paper does not specify any training, validation, or test dataset splits. It describes generating game instances for experiments. |
| Hardware Specification | Yes | Our experiments are conducted on a High Performance Computing (HPC) cluster, with processors are dual E52690v4 (28 cores) and 128 GB memory. |
| Software Dependencies | No | The paper mentions 'Cplex to solve our optimization programs' and 'GAMMUT (http: //gamut.stanford/edu)' but does not provide specific version numbers for these software components. |
| Experiment Setup | Yes | We consider two cases of the defender s deception capability: (i) small deception interval, i.e., αi =βi =0.05; and big deception interval, i.e., αi =βi = 0.15. In Figure 1(a-b), the defender s utility increases while the attacker s utility decreases gradually as the ratio (k/n) increases. |