Ensemble defenses, are widely employed in various security-related
applications to enhance model performance and robustness. The widespread
adoption of these techniques also raises many questions: Are general ensembles
defenses guaranteed to be more robust than individuals? Will stronger adaptive
attacks defeat existing ensemble defense strategies as the cybersecurity arms
race progresses? Can ensemble defenses achieve adversarial robustness to
different types of attacks simultaneously and resist the continually adjusted
adaptive attacks? Unfortunately, these critical questions remain unresolved as
there are no platforms for comprehensive evaluation of ensemble adversarial
attacks and defenses in the cybersecurity domain. In this paper, we propose a
general Cybersecurity Adversarial Robustness Evaluation (CARE) platform aiming
to bridge this gap.

提出了一种名为 Cybersecurity Adversarial Robustness Evaluation（CARE）平台来全面评估集成对抗性攻击和防御的方法，旨在探讨集成防御是否能够提高模型性能和鲁棒性，对不同类型的攻击有效，并抵御不断调整的自适应攻击。