Visible to the public Biblio

Filters: Author is Wang, Qingfeng  [Clear All Filters]
2023-09-01
Xie, Genlin, Cheng, Guozhen, Liang, Hao, Wang, Qingfeng, He, Benwei.  2022.  Evaluating Software Diversity Based on Gadget Feature Analysis. 2022 IEEE 8th International Conference on Computer and Communications (ICCC). :1656—1660.
Evaluating the security gains brought by software diversity is one key issue of software diversity research, but the existing software diversity evaluation methods are generally based on conventional code features and are relatively single, which are difficult to accurately reflect the security gains brought by software diversity. To solve these problems, from the perspective of return-oriented programming (ROP) attack, we present a software diversity evaluation method which integrates metrics for the quality and distribution of gadgets. Based on the proposed evaluation method and SpiderMonkey JavaScript engine, we implement a software diversity evaluation system for compiled languages and script languages. Diversity techniques with different granularities are used to test. The evaluation results show that the proposed evaluation method can accurately and comprehensively reflect the security gains brought by software diversity.
He, Benwei, Guo, Yunfei, Liang, Hao, Wang, Qingfeng, Xie, Genlin.  2022.  Research on Defending Code Reuse Attack Based on Binary Rewriting. 2022 IEEE 8th International Conference on Computer and Communications (ICCC). :1682—1686.
At present, code reuse attacks, such as Return Oriented Programming (ROP), execute attacks through the code of the application itself, bypassing the traditional defense mechanism and seriously threatening the security of computer software. The existing two mainstream defense mechanisms, Address Space Layout Randomization (ASLR), are vulnerable to information disclosure attacks, and Control-Flow Integrity (CFI) will bring high overhead to programs. At the same time, due to the widespread use of software of unknown origin, there is no source code provided or available, so it is not always possible to secure the source code. In this paper, we propose FRCFI, an effective method based on binary rewriting to prevent code reuse attacks. FRCFI first disrupts the program's memory space layout through function shuffling and NOP insertion, then verifies the execution of the control-flow branch instruction ret and indirect call/jmp instructions to ensure that the target address is not modified by attackers. Experiment show shows that FRCFI can effectively defend against code reuse attacks. After randomization, the survival rate of gadgets is only 1.7%, and FRCFI adds on average 6.1% runtime overhead on SPEC CPU2006 benchmark programs.