FPHammer: A Device Identification Framework based on DRAM Fingerprinting

TL;DR

FPHammer introduces a DRAM-based fingerprinting method leveraging Rowhammer-induced bit flips, enabling long-term, stable device identification unaffected by software modifications.

Contribution

The paper presents a novel DRAM fingerprinting technique using Rowhammer to generate stable, unique device fingerprints for long-term tracking.

Findings

High stability of device fingerprints over time

Ability to distinguish devices with identical hardware and software

Effective even after software reinstallation or parameter changes

Abstract

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.