TY - GEN
T1 - Resource Race Attacks on Android
AU - Cai, Yan
AU - Tang, Yutian
AU - Li, Haicheng
AU - Yu, Le
AU - Zhou, Hao
AU - Luo, Xiapu
AU - He, Liang
AU - Su, Purui
PY - 2020/2
Y1 - 2020/2
N2 - Smartphones are frequently involved in accessing private user data. Although many studies have been done to prevent malicious apps from leaking private user data, only a few recent works examine how to remove the sensitive information from the data collected by smartphone hardware resources (e.g., camera). Unfortunately, none of them investigates whether a malicious app can obtain such sensitive information when (or right before/after) a legitimate app collects such data (e.g., taking photos). To fill in the gap, in this paper, we model such attacks as the Resource Race Attack (RRAttack) based on races between two apps during their requests to exclusive resources to access sensitive information. RRAttacks have three categories according to when a race on requesting resources occurs: Pre-Use, In-Use, and Post-Use attacks. We further conduct the first systematic study on the feasibility of launching the RRAttacks on two heavily used exclusive Android resources: camera and touchscreen. In details, we perform Proof-of-Concept (PoC) attacks to reveal that, (a) camera is highly vulnerable to both In-Use and Post-Use attacks; and (b) touchscreen is vulnerable to Pre-Use attacks. Particularly, we demonstrate successful RRAttacks on them to steal private information, to cause financial loss, and to steal user passwords from Android 6 to the latest Android Q. Moreover, our analyses on 1,000 apps indicate that most of them are vulnerable to one to three RRAttacks. Finally, we propose a set of defense strategies against RRAttacks for user apps, system apps, and Android system itself.
AB - Smartphones are frequently involved in accessing private user data. Although many studies have been done to prevent malicious apps from leaking private user data, only a few recent works examine how to remove the sensitive information from the data collected by smartphone hardware resources (e.g., camera). Unfortunately, none of them investigates whether a malicious app can obtain such sensitive information when (or right before/after) a legitimate app collects such data (e.g., taking photos). To fill in the gap, in this paper, we model such attacks as the Resource Race Attack (RRAttack) based on races between two apps during their requests to exclusive resources to access sensitive information. RRAttacks have three categories according to when a race on requesting resources occurs: Pre-Use, In-Use, and Post-Use attacks. We further conduct the first systematic study on the feasibility of launching the RRAttacks on two heavily used exclusive Android resources: camera and touchscreen. In details, we perform Proof-of-Concept (PoC) attacks to reveal that, (a) camera is highly vulnerable to both In-Use and Post-Use attacks; and (b) touchscreen is vulnerable to Pre-Use attacks. Particularly, we demonstrate successful RRAttacks on them to steal private information, to cause financial loss, and to steal user passwords from Android 6 to the latest Android Q. Moreover, our analyses on 1,000 apps indicate that most of them are vulnerable to one to three RRAttacks. Finally, we propose a set of defense strategies against RRAttacks for user apps, system apps, and Android system itself.
KW - Android Privacy
KW - Camera
KW - Resource Race
KW - Touchscreen
UR - http://www.scopus.com/inward/record.url?scp=85083587656&partnerID=8YFLogxK
U2 - 10.1109/SANER48275.2020.9054863
DO - 10.1109/SANER48275.2020.9054863
M3 - Conference article published in proceeding or book
AN - SCOPUS:85083587656
T3 - SANER 2020 - Proceedings of the 2020 IEEE 27th International Conference on Software Analysis, Evolution, and Reengineering
SP - 47
EP - 58
BT - SANER 2020 - Proceedings of the 2020 IEEE 27th International Conference on Software Analysis, Evolution, and Reengineering
A2 - Kontogiannis, Kostas
A2 - Khomh, Foutse
A2 - Chatzigeorgiou, Alexander
A2 - Fokaefs, Marios-Eleftherios
A2 - Zhou, Minghui
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 27th IEEE International Conference on Software Analysis, Evolution, and Reengineering, SANER 2020
Y2 - 18 February 2020 through 21 February 2020
ER -