@Article{cmc.2018.02574,
AUTHOR = {Lin  Chen, Chunfang  Yang, Fenlin  Liu, Daofu  Gong, Shichang  Ding},
TITLE = {Automatic Mining of Security-Sensitive Functions from Source Code},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {56},
YEAR = {2018},
NUMBER = {2},
PAGES = {199--210},
URL = {http://www.techscience.com/cmc/v56n2/22929},
ISSN = {1546-2226},
ABSTRACT = {When dealing with the large-scale program, many automatic vulnerability mining techniques encounter such problems as path explosion, state explosion, and low efficiency. Decomposition of large-scale programs based on safety-sensitive functions helps solve the above problems. And manual identification of security-sensitive functions is a tedious task, especially for the large-scale program. This study proposes a method to mine security-sensitive functions the arguments of which need to be checked before they are called. Two argument-checking identification algorithms are proposed based on the analysis of two implementations of argument checking. Based on these algorithms, security-sensitive functions are detected based on the ratio of invocation instances the arguments of which have been protected to the total number of instances. The results of experiments on three well-known open-source projects show that the proposed method can outperform competing methods in the literature.},
DOI = {10.3970/cmc.2018.02574}
}