Multi-Defender Strategic Filtering Against Spear-Phishing Attacks

Authors: Aron Laszka, Jian Lou, Yevgeniy Vorobeychik

AAAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical We characterize both Stackelberg multi-defender equilibria, corresponding to short-term strategic dynamics, as well as Nash equilibria of the simultaneous game between all users and the attacker, modeling long-term dynamics, and exhibit a polynomial-time algorithm for computing short-term (Stackelberg) equilibria. We find that while Stackelberg multi-defender equilibrium need not exist, Nash equilibrium always exists, and remarkably, both equilibria are unique and socially optimal.
Researcher Affiliation Academia Aron Laszka Electrical Engineering and Computer Sciences Dept. University of California, Berkeley Berkeley, CA Jian Lou and Yevgeniy Vorobeychik Institute for Software Integrated Systems Dept. of Electrical Engineering and Computer Science Vanderbilt University Nashville, TN
Pseudocode Yes Algorithm 1 Find a Stackelberg Multi-Defender Equilibrium (SMDE) input: a set of users U, Lu, L1 u(fu) and L0 u(fu) for every user u, and A for attacker return: a SMDE or there is no SMDE
Open Source Code No The paper does not provide any specific links or statements about the availability of open-source code for the described methodology.
Open Datasets No The paper is theoretical and does not conduct experiments that involve training on a dataset. While it mentions the UCI and Enron datasets in reference to prior work's tradeoff curves (Figure 1), it does not use them for its own experimental training or provide access information for this paper's work.
Dataset Splits No The paper is theoretical and does not conduct experiments that would involve training, validation, or test splits of data.
Hardware Specification No The paper does not provide any hardware specifications for running experiments, as it focuses on theoretical analysis and algorithm design.
Software Dependencies No The paper does not list any 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.