Infrared imaging systems have a vast array of potential applications in pedestrian detection and autonomous driving, and their safety performance is of great concern. However, few studies have explored the safety of infrared imaging systems in real-world settings. Previous research has used physical perturbations such as small bulbs and thermal "QR codes" to attack infrared imaging detectors, but such methods are highly visible and lack stealthiness. Other researchers have used hot and cold blocks to deceive infrared imaging detectors, but this method is limited in its ability to execute attacks from various angles. To address these shortcomings, we propose a novel physical attack called adversarial infrared blocks (AdvIB). By optimizing the physical parameters of the adversarial infrared blocks, this method can execute a stealthy black-box attack on thermal imaging system from various angles. We evaluate the proposed method based on its effectiveness, stealthiness, and robustness. Our physical tests show that the proposed method achieves a success rate of over 80% under most distance and angle conditions, validating its effectiveness. For stealthiness, our method involves attaching the adversarial infrared block to the inside of clothing, enhancing its stealthiness. Additionally, we test the proposed method on advanced detectors, and experimental results demonstrate an average attack success rate of 51.2%, proving its robustness. Overall, our proposed AdvIB method offers a promising avenue for conducting stealthy, effective and robust black-box attacks on thermal imaging system, with potential implications for real-world safety and security applications.

翻译：红外成像系统在行人检测和自动驾驶等领域具有广泛潜在应用，其安全性能备受关注。然而，现有研究较少探索红外成像系统在真实环境中的安全性问题。以往研究采用小灯泡和热"QR码"等物理扰动攻击红外成像探测器，但此类方法可见性高且缺乏隐蔽性。另一些研究者使用冷热块欺骗红外成像探测器，但该方法难以从多角度实施攻击。为解决上述不足，我们提出一种名为对抗性红外块（AdvIB）的新型物理攻击方法。通过优化对抗性红外块的物理参数，该方法能从多角度对热成像系统实施隐蔽性黑盒攻击。我们从有效性、隐蔽性和鲁棒性三个维度评估所提方法。物理测试表明，多数距离和角度条件下该方法攻击成功率超过80%，验证了其有效性。在隐蔽性方面，该方法将对抗性红外块附着于衣物内侧，增强了攻击的隐蔽性。此外，我们在先进探测器上测试所提方法，实验结果显示平均攻击成功率达51.2%，证明了其鲁棒性。总体而言，所提AdvIB方法为对热成像系统实施隐蔽、有效且鲁棒的黑盒攻击提供了新途径，对现实世界安全应用具有潜在价值。