Update 2022asplos cite.bib with ACM bibtex data

content/publication/2022-mobile-gpu-eavesdropping/cite.bib

@@ -1,7 +1,17 @@
-@inproceedings{yang2022eavesdropping,
-  title={Eavesdropping user credentials via GPU side channels on smartphones},
-  author={Yang, Boyuan and Chen, Ruirong and Huang, Kai and Yang, Jun and Gao, Wei},
-  booktitle={Proceedings of the 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems},
-  pages={285--299},
-  year={2022}
+@inproceedings{10.1145/3503222.3507757,
+author = {Yang, Boyuan and Chen, Ruirong and Huang, Kai and Yang, Jun and Gao, Wei},
+title = {Eavesdropping user credentials via GPU side channels on smartphones},
+year = {2022},
+isbn = {9781450392051},
+publisher = {Association for Computing Machinery},
+address = {New York, NY, USA},
+url = {https://doi.org/10.1145/3503222.3507757},
+doi = {10.1145/3503222.3507757},
+abstract = {Graphics Processing Unit (GPU) on smartphones is an effective target for hardware attacks. In this paper, we present a new side channel attack on mobile GPUs of Android smartphones, allowing an unprivileged attacker to eavesdrop the user's credentials, such as login usernames and passwords, from their inputs through on-screen keyboard. Our attack targets on Qualcomm Adreno GPUs and investigate the amount of GPU overdraw when rendering the popups of user's key presses of inputs. Such GPU overdraw caused by each key press corresponds to unique variations of selected GPU performance counters, from which these key presses can be accurately inferred. Experiment results from practical use on multiple models of Android smartphones show that our attack can correctly infer more than 80\% of user's credential inputs, but incur negligible amounts of computing overhead and network traffic on the victim device. To counter this attack, this paper suggests mitigations of access control on GPU performance counters, or applying obfuscations on the values of GPU performance counters.},
+booktitle = {Proceedings of the 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems},
+pages = {285–299},
+numpages = {15},
+keywords = {Input Eavesdropping, Mobile GPU, Performance Counters, Side Channel, Smartphones},
+location = {Lausanne, Switzerland},
+series = {ASPLOS '22}
 }