Detection Technique of Software-induced Rowhammer Attacks

Abstract

Side-channel attacks have recently progressed into software-induced attacks. In particular, a rowhammer attack, which exploits the characteristics of dynamic random access memory (DRAM), can quickly and continuously access the cells as the cell density of DRAM increases, thereby generating a disturbance error affecting the neighboring cells, resulting in bit flips. Although a rowhammer attack is a highly sophisticated attack in which disturbance errors are deliberately generated into data bits, it has been reported that it can be exploited on various platforms such as mobile devices, web browsers, and virtual machines. Furthermore, there have been studies on bypassing the defense measures of DRAM manufacturers and the like to respond to rowhammer attacks. A rowhammer attack can control user access and compromise the integrity of sensitive data with attacks such as a privilege escalation and an alteration of the encryption keys. In an attempt to mitigate a rowhammer attack, various hardware- and software-based mitigation techniques are being studied, but there are limitations in that the research methods do not detect the rowhammer attack in advance, causing overhead or degradation of the system performance. Therefore, in this study, a rowhammer attack detection technique is proposed by extracting common features of rowhammer attack files through a static analysis of rowhammer attack codes.