Biblio

Filters: Author is Guan, Le  [Clear All Filters]
2023-02-17
Shi, Jiameng, Guan, Le, Li, Wenqiang, Zhang, Dayou, Chen, Ping, Zhang, Ning.  2022.  HARM: Hardware-Assisted Continuous Re-randomization for Microcontrollers. 2022 IEEE 7th European Symposium on Security and Privacy (EuroS&P). :520–536.
Microcontroller-based embedded systems have become ubiquitous with the emergence of IoT technology. Given its critical roles in many applications, its security is becoming increasingly important. Unfortunately, MCU devices are especially vulnerable. Code reuse attacks are particularly noteworthy since the memory address of firmware code is static. This work seeks to combat code reuse attacks, including ROP and more advanced JIT-ROP via continuous randomization. Previous proposals are geared towards full-fledged OSs with rich runtime environments, and therefore cannot be applied to MCUs. We propose the first solution for ARM-based MCUs. Our system, named HARM, comprises a secure runtime and a binary analysis tool with rewriting module. The secure runtime, protected inside the secure world, proactively triggers and performs non-bypassable randomization to the firmware running in a sandbox in the normal world. Our system does not rely on any firmware feature, and therefore is generally applicable to both bare-metal and RTOS-powered firmware. We have implemented a prototype on a development board. Our evaluation results indicate that HARM can effectively thaw code reuse attacks while keeping the performance and energy overhead low.
2020-01-27
Guan, Le, Cao, Chen, Zhu, Sencun, Lin, Jingqiang, Liu, Peng, Xia, Yubin, Luo, Bo.  2019.  Protecting mobile devices from physical memory attacks with targeted encryption. Proceedings of the 12th Conference on Security and Privacy in Wireless and Mobile Networks. :34–44.
Sensitive data in a process could be scattered over the memory of a computer system for a prolonged period of time. Unfortunately, DRAM chips were proven insecure in previous studies. The problem becomes worse in the mobile environment, in which users' smartphones are easily lost or stolen. The powered-on phones may contain sensitive data in the vulnerable DRAM chips. In this paper, we propose MemVault, a mechanism to protect sensitive data in Android devices against physical memory attacks. MemVault keeps track of the propagation of well-marked sensitive data sources, and selectively encrypts tainted sensitive memory contents in the DRAM chip. When a tainted object is accessed, MemVault redirects the access to the internal RAM (iRAM), where the cipher-text object is decrypted transparently. iRAM is a system-on-chip (SoC) component which is by nature immune to physical memory exploits. We have implemented a MemVault prototype system, and have evaluated it with extensive experiments. Our results validate that MemVault effectively eliminates the occurrences of clear-text sensitive objects in DRAM chips, and imposes acceptable overheads.
2018-01-23
Guan, Le, Jia, Shijie, Chen, Bo, Zhang, Fengwei, Luo, Bo, Lin, Jingqiang, Liu, Peng, Xing, Xinyu, Xia, Luning.  2017.  Supporting Transparent Snapshot for Bare-metal Malware Analysis on Mobile Devices. Proceedings of the 33rd Annual Computer Security Applications Conference. :339–349.

The increasing growth of cybercrimes targeting mobile devices urges an efficient malware analysis platform. With the emergence of evasive malware, which is capable of detecting that it is being analyzed in virtualized environments, bare-metal analysis has become the definitive resort. Existing works mainly focus on extracting the malicious behaviors exposed during bare-metal analysis. However, after malware analysis, it is equally important to quickly restore the system to a clean state to examine the next sample. Unfortunately, state-of-the-art solutions on mobile platforms can only restore the disk, and require a time-consuming system reboot. In addition, all of the existing works require some in-guest components to assist the restoration. Therefore, a kernel-level malware is still able to detect the presence of the in-guest components. We propose Bolt, a transparent restoration mechanism for bare-metal analysis on mobile platform without rebooting. Bolt achieves a reboot-less restoration by simultaneously making a snapshot for both the physical memory and the disk. Memory snapshot is enabled by an isolated operating system (BoltOS) in the ARM TrustZone secure world, and disk snapshot is accomplished by a piece of customized firmware (BoltFTL) for flash-based block devices. Because both the BoltOS and the BoltFTL are isolated from the guest system, even kernel-level malware cannot interfere with the restoration. More importantly, Bolt does not require any modifications into the guest system. As such, Bolt is the first that simultaneously achieves efficiency, isolation, and stealthiness to recover from infection due to malware execution. We have implemented a Bolt prototype working with the Android OS. Experimental results show that Bolt can restore the guest system to a clean state in only 2.80 seconds.