Name
Abstract | ||
|---|---|---|
The Android packaging model offers adequate opportunities for attackers to inject malicious code into popular benign apps, attempting to develop new malicious apps that can then be easily spread to a large user base. Despite the fact that the literature has already presented a number of tools to detect piggybacked apps, there is still lacking a comprehensive investigation on the piggybacking processes. To fill this gap, in this work, we collect a large set of benign/piggybacked app pairs that can be taken as benchmark apps for further investigation. We manually look into these benchmark pairs for understanding the characteristics of piggybacking apps and eventually we report 20 interesting findings. We expect these findings to initiate new research directions such as practical and scalable piggybacked app detection, explainable malware detection, and malicious code location. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/ICSE-C.2017.109 | ICSE (Companion Volume) |
Field | DocType | ISSN |
Piggybacking (Internet access),Android app,World Wide Web,Android (operating system),Computer security,Computer science,Model-driven architecture,Malware,Benchmark (computing),Payload,Scalability | Conference | 2574-1926 |
Citations | PageRank | References |
6 | 0.42 | 28 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Li Li | 1 | 247 | 14.41 |
| daoyuan li | 2 | 74 | 5.71 |
| Tegawendé F. Bissyandé | 3 | 863 | 63.90 |
| Jacques Klein | 4 | 2498 | 112.20 |
| Yves Le Traon | 5 | 155 | 14.08 |
| David Lo | 6 | 5346 | 259.67 |
| Lorenzo Cavallaro | 7 | 886 | 52.85 |