论文标题
FPHAMER:基于DRAM指纹识别的设备标识框架
FPHammer: A Device Identification Framework based on DRAM Fingerprinting
论文作者
论文摘要
设备指纹技术根据设备的硬件特性提取指纹以识别设备。设备指纹的主要目标是准确而独特地识别设备,这需要生成的设备指纹具有良好的稳定性来实现目标设备的长期跟踪。但是,某些现有的指纹技术产生的指纹不够稳定或经常变化,因此无法长时间跟踪目标设备。在本文中,我们提出了Fphammer,这是一种基于DRAM的新型指纹技术。我们技术生成的设备指纹具有很高的稳定性,可用于长时间跟踪设备。我们利用Rowhammer技术反复并快速访问DRAM的一排,以在其相邻行中获得位。然后,我们基于收集的位翻转位置构建设备的物理指纹。物理指纹的唯一性和可靠性的评估结果表明,它可用于区分具有相同硬件和软件配置的设备。设备识别的实验结果表明,我们创新技术产生的物理指纹与整个设备而不仅仅是DRAM模块固有地链接。即使设备修改了软件级别的参数,例如MAC地址和IP地址,甚至重新安装了操作系统,我们也可以准确识别目标设备。这表明Fphammer可以生成不受软件层参数影响的稳定指纹。
The device fingerprinting technique extracts fingerprints based on the hardware characteristics of the device to identify the device. The primary goal of device fingerprinting is to accurately and uniquely identify a device, which requires the generated device fingerprints to have good stability to achieve long-term tracking of the target device. However, the fingerprints generated by some existing fingerprinting technologies are not stable enough or change frequently, making it impossible to track the target device for a long time. In this paper, we present FPHammer, a novel DRAM-based fingerprinting technique. The device fingerprint generated by our technique has high stability and can be used to track the device for a long time. We leverage the Rowhammer technique to repeatedly and quickly access a row in DRAM to get bit flips in its adjacent row. We then construct a physical fingerprint of the device based on the locations of the collected bit flips. The evaluation results of the uniqueness and reliability of the physical fingerprint show that it can be used to distinguish devices with the same hardware and software configuration. The experimental results on device identification demonstrate that the physical fingerprints engendered by our innovative technique are inherently linked to the entirety of the device rather than just the DRAM module. Even if the device modifies software-level parameters such as MAC address and IP address or even reinstalls the operating system, we can accurately identify the target device. This demonstrates that FPHammer can generate stable fingerprints that are not affected by software layer parameters.