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.
| Original language | English |
|---|---|
| Title of host publication | Proceedings |
| Subtitle of host publication | 2017 IEEE/ACM 39th International Conference on Software Engineering Companion - ICSE-C 2017 |
| Editors | Alessandro Orso, Martin Robillard |
| Place of Publication | Piscataway NJ USA |
| Publisher | IEEE, Institute of Electrical and Electronics Engineers |
| Pages | 359-361 |
| Number of pages | 3 |
| ISBN (Print) | 9781538615898 |
| DOIs | |
| Publication status | Published - 30 Jun 2017 |
| Externally published | Yes |
| Event | International Conference on Software Engineering 2017 - Buenos Aires, Argentina Duration: 20 May 2017 → 28 May 2017 Conference number: 39th http://icse2017.gatech.edu/ |
Conference
| Conference | International Conference on Software Engineering 2017 |
|---|---|
| Abbreviated title | ICSE-C 2017 |
| Country | Argentina |
| City | Buenos Aires |
| Period | 20/05/17 → 28/05/17 |
| Other | IEEE/ACM International Conference on Software Engineering Companion (ICSE-C 2017) |
| Internet address |
Cite this
}
Understanding android app piggybacking. / Li, Li; Li, Daoyuan; Bissyande, Tegawende F.; Klein, Jacques; Le Traon, Yves; Lo, David; Cavallaro, Lorenzo.
Proceedings: 2017 IEEE/ACM 39th International Conference on Software Engineering Companion - ICSE-C 2017. ed. / Alessandro Orso; Martin Robillard. Piscataway NJ USA : IEEE, Institute of Electrical and Electronics Engineers, 2017. p. 359-361 7965358.Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Other
TY - GEN
T1 - Understanding android app piggybacking
AU - Li, Li
AU - Li, Daoyuan
AU - Bissyande, Tegawende F.
AU - Klein, Jacques
AU - Le Traon, Yves
AU - Lo, David
AU - Cavallaro, Lorenzo
PY - 2017/6/30
Y1 - 2017/6/30
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85026776815&partnerID=8YFLogxK
U2 - 10.1109/ICSE-C.2017.109
DO - 10.1109/ICSE-C.2017.109
M3 - Conference Paper
AN - SCOPUS:85026776815
SN - 9781538615898
SP - 359
EP - 361
BT - Proceedings
A2 - Orso, Alessandro
A2 - Robillard, Martin
PB - IEEE, Institute of Electrical and Electronics Engineers
CY - Piscataway NJ USA
ER -