| Title | Research on Mobile Application Local Denial of Service Vulnerability Detection Technology Based on Rule Matching |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Chen, Lu, Ma, Yuanyuan, SHAO, Zhipeng, CHEN, Mu |
| Conference Name | 2019 IEEE International Conference on Energy Internet (ICEI) |
| Keywords | -dynamic-detection, -rule-matching, -security-vulnerability, -static-detection, Communication networks, compositionality, Computer crashes, dynamic detection method, feature extraction, formal verification, hook verification, Human Behavior, invasive software, local denial of service vulnerability detection technology, malicious application flooding, Metrics, mobile application market, mobile applications, mobile computing, mobile-application, Monitoring, Pattern matching, pubcrawl, Resiliency, rule matching, security, smali abstract syntax tree, smart phones, static detection method, vulnerability detection |
| Abstract | Aiming at malicious application flooding in mobile application market, this paper proposed a method based on rule matching for mobile application local denial of service vulnerability detection. By combining the advantages of static detection and dynamic detection, static detection adopts smali abstract syntax tree as rule matching object. This static detection method has higher code coverage and better guarantees the integrity of mobile application information. The dynamic detection performs targeted hook verification on the static detection result, which improves the accuracy of the detection result and saves the test workload at the same time. This dynamic detection method has good scalability, can be upgraded with discovery and variants of the vulnerability. Through experiments, it is verified that the mobile application with this vulnerability can be accurately found in a large number of mobile applications, and the effectiveness of the system is verified. |
| DOI | 10.1109/ICEI.2019.00109 |
| Citation Key | chen_research_2019 |
Research on Mobile Application Local Denial of Service Vulnerability Detection Technology Based on Rule Matching