Adversarial Infrared Geometry: Utilising Geometric Properties for Efficient Attacks on Infrared Pedestrian Detectors

Infrared imaging technology holds a prominent position across various applications, particularly with the burgeoning significance of infrared object detection technology. Although prior research has explored physical attacks on infrared object detectors, the practical implementation of these techniques remains intricate. For example, certain methodologies involve the deployment of specialised equipment such as bulb boards or infrared QR suits to execute attacks, necessitating costly optimisation and cumbersome deployment processes. Alternatively, other strategies employ irregular aerogel as physical perturbations for infrared attacks, albeit with associated optimisation expenses and perceptibility issues. In this study, we introduce a novel infrared physical attack termed ‘adversarial infrared geometry’ (AdvIG), which enables efficient black‐box query attacks by modelling diverse geometric shapes such as lines, triangles and ellipses and optimising their physical parameters using particle swarm optimisation (PSO). We conduct extensive experiments to assess the effectiveness, stealthiness and robustness of AdvIG. In digital attack experiments, line, triangle and ellipse patterns achieve success rates of 93.1%, 86.8% and 100.0%, respectively, with average query times of 71.7, 113.1 and 2.6, respectively, thereby confirming the efficiency of AdvIG. Physical attack experiments are performed to evaluate the success rate of AdvIG at various distances. On average, the success rates for lines, triangles and ellipses are 61.1%, 61.2% and 96.2%, respectively. We further conduct comprehensive experiments to analyse AdvIG, including ablation experiments, transfer attack experiments and assessments of adversarial defence mechanisms. Given the superior performance of our method as a simple and efficient black‐box adversarial attack in both digital and physical environments, we advocate broader attention to AdvIG.