State-of-the-art solutions detect jamming attacks ex-post, i.e., only when jamming has already disrupted the wireless communication link. In many scenarios, e.g., mobile networks or static deployments distributed over a large geographical area, it is often desired to detect jamming at the early stage, when it affects the communication link enough to be detected but not sufficiently to disrupt it (detection of weak jamming signals). Under such assumptions, devices can enhance situational awareness and promptly apply mitigation, e.g., moving away from the jammed area in mobile scenarios or changing communication frequency in static deployments, before jamming fully disrupts the communication link. Although some contributions recently demonstrated the feasibility of detecting low-power and weak jamming signals, they make simplistic assumptions far from real-world deployments. Given the current state of the art, no evidence exists that detection of weak jamming can be considered with real-world communication technologies. In this paper, we provide and comprehensively analyze new general-purpose strategies for detecting weak jamming signals, compatible by design with one of the most relevant communication technologies used by commercial-off-the-shelf devices, i.e., IEEE 802.11. We describe two operational modes: (i) binary classification via Convolutional Neural Networks and (ii) one-class classification via Sparse Autoencoders. We evaluate and compare the proposed approaches with the current state-of-the-art using data collected through an extensive real-world experimental campaign in three relevant environments. At the same time, we made the dataset available to the public. Our results demonstrate that detecting weak jamming signals is feasible in all considered real-world environments, and we provide an in-depth analysis considering different techniques, scenarios, and mobility patterns.

翻译：现有最先进的解决方案仅在干扰已经破坏无线通信链路后进行事后检测。在许多场景中，例如移动网络或分布在广阔地理区域的静态部署，通常希望在干扰的早期阶段进行检测，即当干扰对通信链路的影响足以被检测到但尚不足以完全破坏链路时（弱干扰信号的检测）。在此类假设下，设备可以增强态势感知能力，并在干扰完全破坏通信链路之前及时采取缓解措施，例如在移动场景中远离干扰区域，或在静态部署中改变通信频率。尽管近期一些研究已证明检测低功率弱干扰信号的可行性，但它们所做的假设过于简化，与真实世界部署相去甚远。鉴于当前技术水平，尚无证据表明弱干扰检测可在实际通信技术中实现。本文提出并全面分析了用于检测弱干扰信号的新通用策略，其设计兼容商用现货设备最常用的通信技术之一——IEEE 802.11。我们描述了两种操作模式：（i）通过卷积神经网络进行二元分类，以及（ii）通过稀疏自编码器进行单类分类。我们利用在三种典型环境中通过大规模真实世界实验活动收集的数据，对所提方法与当前最先进技术进行了评估比较。同时，我们已将数据集公开。研究结果表明，在所有考虑的真实世界环境中检测弱干扰信号是可行的，并针对不同技术、场景和移动模式提供了深入分析。