Electromagnetic (EM) side-channel analysis traditionally assumes a stationary, close-proximity probe - a threat model that underestimates aerial adversaries. TriSweep is a simulation framework that designs and evaluates a four-drone swarm architecture for autonomous standoff EM-SCA of embedded microcontrollers at 0.25-1.5 m. Three spatially specialized collector drones - Anchor (full-spectrum), Mask Probe (mask-register loading leakage), and Cipher Probe (masked SubBytes output leakage) - feed a stationary Accumulator drone that performs coherent combining (+4.8 dB SNR gain) and second-order mask cancellation via a centered product of the two spatially separated leakage streams. Evaluated against three real ANSSI ASCAD datasets (ATmega8515 masked AES-128 and 50/100-sample desynchronized variants), the framework achieves a simulated key rank of 18 +/- 1.7 (five-seed) at 0.25 m on the primary masked dataset. Profiling-trace cross-correlation alignment reduces single-drone rank from 89 to 21 on the 100-sample-jitter variant, demonstrating compensation for drone hover vibration. A two-channel CNN in the Accumulator converges to a loss of 0.454 (vs. random baseline 5.545) and improves rank on desynchronized datasets. No physical hardware has been fabricated; prototype construction is the planned next step.

翻译：电磁（EM）侧信道分析传统上假设使用固定且近距离的探头——这一威胁模型低估了空中对抗手段。TriSweep是一个仿真框架，用于设计并评估一种四无人机蜂群架构，可在0.25-1.5米的距离上对嵌入式微控制器进行自主非接触式电磁侧信道分析（EM-SCA）。三架空间分工的采集无人机——锚点无人机（全频谱）、掩码探头无人机（掩码寄存器加载泄露）和密文探头无人机（掩码SubBytes输出泄露）——将数据馈送至一架固定的汇聚无人机，该无人机通过两路空间分离泄露流的中心积实现相干合并（+4.8 dB信噪比增益）与二阶掩码消除。基于三个真实的ANSSI ASCAD数据集（ATmega8515掩码AES-128及50样本/100样本去同步化变体）进行评估，该框架在主要掩码数据集上于0.25米处实现了18 ± 1.7（五种子播种）的模拟密钥排名。通过训练迹互相关对齐，在100样本抖动变体上将单无人机排名从89改善至21，表明其能够补偿无人机悬停振动。汇聚无人机中的双通道卷积神经网络（CNN）损失收敛至0.454（随机基线为5.545），并在去同步化数据集上提升了密钥排名。目前未制造物理硬件；原型构建为下一步计划。