基于Rowhammer 物理不可克隆函数的物理设备测绘框架

The core problem of cyberspace mapping is to identify accurately and track dynamically devices. However, with the development of anonymization technology, devices can have multiple IP addresses and MAC addresses. This makes it increasingly difficult to map multiple virtual attributes to the same physical device through traditional mapping techniques. In this paper, a mapping framework based on Physical Unclonable Function (PUF) is proposed which can actively detect physical resources in cyberspace and track dynamically devices based on physical fingerprints to construct resource portraits. Furthermore, a new method is proposed to implement the Rowhammer-based Dynamic Random-Access Memory Physical Unclonable Function (DRAM PUF) on a regular Personal Computer (PC) equipped with Double Data Rate Fourth (DDR4) memory. Performance evaluation shows that the response extracted from the Rowhammer PUF on the PC using the proposed method is unique and reliable, and can be used as a unique physical fingerprint of the device. Experimental results show that even if the target device modifies its MAC address, IP address, or reinstalls operating system, the framework proposed in this paper can still accurately identify the target device by constructing a physical fingerprint database for device matching.