A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf
.
Predicting sensitive information leakage in IoT applications using flows-aware machine learning approach
[article]
2022
arXiv
pre-print
This paper presents an approach for identification of vulnerable IoT applications. The approach focuses on a category of vulnerabilities that leads to sensitive information leakage which can be identified by using taint flow analysis. Tainted flows vulnerability is very much impacted by the structure of the program and the order of the statements in the code, designing an approach to detect such vulnerability needs to take into consideration such information in order to provide precise results.
arXiv:2201.02677v1
fatcat:cd5k6dlmjjgohoasv6hsvqwqve