An Empirical Study of Android Security Bulletins in Different Vendors

April 2020·
Sadegh Farhang
,
Mehmet Bahadir Kirdan
Aron Laszka
Aron Laszka
,
Jens Grossklags
Abstract
Mobile devices encroach on almost every part of our lives, including work and leisure, and contain a wealth of personal and sensitive information. It is, therefore, imperative that these devices uphold high security standards. A key aspect is the security of the underlying operating system. In particular, Android plays a critical role due to being the most dominant platform in the mobile ecosystem with more than one billion active devices and due to its openness, which allows vendors to adopt and customize it. Similar to other platforms, Android maintains security by providing monthly security patches and announcing them via the Android security bulletin. To absorb this information successfully across the Android ecosystem, impeccable coordination by many different vendors is required. In this paper, we perform a comprehensive study of 3,171 Android-related vulnerabilities and study to which degree they are reflected in the Android security bulletin, as well as in the security bulletins of three leading vendors: Samsung, LG, and Huawei. In our analysis, we focus on the metadata of these security bulletins (e.g., timing, affected layers, severity, and CWE data) to better understand the similarities and differences among vendors. We find that (i) the studied vendors in the Android ecosystem have adopted different structures for vulnerability reporting, (ii) vendors are less likely to react with delay for CVEs with Android Git repository references, (iii) vendors handle Qualcomm-related CVEs different from the rest of external layer CVEs.
Type
Venue
The Web Conference (WWW 2020), 3063–3069
publications

Acceptance Rate: 19%

Authors

Aron Laszka
Associate Professor

Aron Laszka is an Associate Professor in the College of Information Sciences and Technology at the Pennsylvania State University. Previously, he was an Assistant Professor at the University of Houston, a Research Assistant Professor at Vanderbilt University, and a Postdoctoral Scholar at the University of California, Berkeley.

His research interests revolve around artificial intelligence and cyber-physical systems, focusing on machine learning for decision making and optimization, with applications in smart and connected communities, critical infrastructure, and cybersecurity.

His research is funded by the National Science Foundation, the Department of Energy, the Department of Transportation, and other agencies.