论文标题
Ictgan-一种用于基于加速度计的步态身份验证系统的随机向量攻击的攻击缓解技术
iCTGAN--An Attack Mitigation Technique for Random-vector Attack on Accelerometer-based Gait Authentication Systems
论文作者
论文摘要
最近的一项研究表明，基于加速度计的步态身份验证系统（$ v $ abgait）通常（香草）研究的实现容易受到随机矢量攻击的影响。同一项研究提出了Beta噪声辅助实施（$β$ abgait）来减轻攻击。在本文中，我们使用三个基于加速度计的步态数据集评估了对$ v $ abgait和$β$ abgait的随机向量攻击的有效性。此外，我们提出了$ i $ abgait，这是Abgait的另一种实现，该实现使用条件表格生成的对抗网络。然后，我们评估了$ i $ i $ abgait对传统的零富特和随机矢量攻击的弹性。结果表明，在大多数实验环境中，$ i $ abgait在合理程度上减轻了随机矢量攻击的影响，并优于$β$ abgait。
A recent study showed that commonly (vanilla) studied implementations of accelerometer-based gait authentication systems ($v$ABGait) are susceptible to random-vector attack. The same study proposed a beta noise-assisted implementation ($β$ABGait) to mitigate the attack. In this paper, we assess the effectiveness of the random-vector attack on both $v$ABGait and $β$ABGait using three accelerometer-based gait datasets. In addition, we propose $i$ABGait, an alternative implementation of ABGait, which uses a Conditional Tabular Generative Adversarial Network. Then we evaluate $i$ABGait's resilience against the traditional zero-effort and random-vector attacks. The results show that $i$ABGait mitigates the impact of the random-vector attack to a reasonable extent and outperforms $β$ABGait in most experimental settings.
