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22. Hard-coded backdoor detection method based on semantic conflict

Author

Anxiang HU, Da XIAO, Shichen GUO, Shengli LIU

Subjects
router firmware, hard-coded backdoor, string comparison functions, semantic conflict, Electronic computers. Computer science, QA75.5-76.95
Abstract

The current router security issues focus on the mining and utilization of memory-type vulnerabilities, but there is low interest in detecting backdoors.Hard-coded backdoor is one of the most common backdoors, which is simple and convenient to set up and can be implemented with only a small amount of code.However, it is difficult to be discovered and often causes serious safety hazard and economic loss.The triggering process of hard-coded backdoor is inseparable from string comparison functions.Therefore, the detection of hard-coded backdoors relies on string comparison functions, which are mainly divided into static analysis method and symbolic execution method.The former has a high degree of automation, but has a high false positive rate and poor detection results.The latter has a high accuracy rate, but cannot automate large-scale detection of firmware, and faces the problem of path explosion or even unable to constrain solution.Aiming at the above problems, a hard-coded backdoor detection algorithm based on string text semantic conflict (Stect) was proposed since static analysis and the think of stain analysis.Stect started from the commonly used string comparison functions, combined with the characteristics of MIPS and ARM architectures, and extracted a set of paths with the same start and end nodes using function call relationships, control flow graphs, and branching selection dependent strings.If the strings in the successfully verified set of paths have semantic conflict, it means that there is a hard-coded backdoor in the router firmware.In order to evaluate the detection effect of Stect, 1 074 collected device images were tested and compared with other backdoor detection methods.Experimental results show that Stect has a better detection effect compared with existing backdoor detection methods including Costin and Stringer: 8 hard-coded backdoor images detected from image data set, and the recall rate reached 88.89%.

Published
2023
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36. Coupled effects of heavy rainfall and falling water‐level exhibit the most significant influences on reservoir bank failures.

Author

Li, Yihang, Xu, Xiangzhou, and Guo, Shengli

Subjects
RAINFALL anomalies, RAINFALL, WATER waves, BANK failures, LANDFORMS
Abstract

Mass failures are often induced or activated by the variation of hydrological factors within a reservoir area. Clarifying the relationships between the failure volume and different hydrological factors may help to identify both the dominant factors influencing reservoir bank failures and the most hazardous combinations of factors inducing such events. This study examines the influence of different hydrological factors on bank failures using model experiments incorporating variations in rainfall, wave and water level. The results indicate that the coupled effects of heavy rainfall and falling water‐level had the most significant impact on bank failure. The cumulative failure mass of the reservoir bank peaked at 177.2 × 103 cm3 under the coupled effects of rainfall and falling water‐level. In comparison, the cumulative mass failures on the reservoir bank under rainfall superimposed onto waves and rainfall superimposed onto water level rise were 162.4 × 103 and 129.2 × 103 cm3, respectively. The impact of heavy rainfall significantly contributed the mass failures on soil reservoir bank. The analysis reveals that the highest cumulative failure, 106.3 × 103 cm3, occurred during periods of heavy rainfall. Compared with heavy rainfall, the cumulative failure volumes in the reservoir experienced a reduction of 46% and 55% under solely declining and solely rising reservoir water levels, respectively. The early phases of changing hydrological conditions have a significant effect on the stability of the soil reservoir bank. Mass failures on the bank predominantly occurred during the initial three events of the five simulation experiments performed for each landform, which could account for up to 87% of the total volume. Hence, it is advisable to avoid lowering reservoir water levels during periods of sustained heavy rainfall in order to mitigate the risk of bank failure. [ABSTRACT FROM AUTHOR]

Published
2024
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