Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1].
Lazy Defenders Are Almost Optimal against Diligent Attackers
Authors: Avrim Blum, Nika Haghtalab, Ariel Procaccia
AAAI 2014 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We analytically demonstrate that in zero-sum security games, lazy defenders, who simply keep optimizing against perfectly informed attackers, are almost optimal against diligent attackers, who go to the effort of gathering a reasonable number of observations. This result implies that, in some realistic situations, limited surveillance may not need to be explicitly addressed. But rather than designing new or improved algorithms, as is common in the security games literature, we take the opposite approach by analytically demonstrating that, in realistic situations, limited surveillance may not be a major concern. |
| Researcher Affiliation | Academia | Avrim Blum Computer Science Department Carnegie Mellon University EMAIL; Nika Haghtalab Computer Science Department Carnegie Mellon University EMAIL; Ariel D. Procaccia Computer Science Department Carnegie Mellon University EMAIL |
| Pseudocode | No | No pseudocode or algorithm blocks were found in the paper. |
| Open Source Code | No | The paper does not mention providing open-source code for its methodology. |
| Open Datasets | No | The paper is theoretical and presents mathematical models and proofs rather than using empirical datasets for training. Therefore, no information about publicly available training datasets is provided. |
| Dataset Splits | No | The paper is theoretical and does not describe empirical experiments with data splits for training, validation, or testing. |
| Hardware Specification | No | The paper is theoretical and does not mention any hardware specifications used for experiments. |
| Software Dependencies | No | The paper is theoretical and does not mention specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe an experimental setup with hyperparameters or system-level training settings. |