Targeted Deanonymization via the Cache Side Channel: Attacks and Defenses
.
2022. Targeted Deanonymization via the Cache Side Channel: Attacks and Defenses. 31st USENIX Security Symposium (USENIX Security 22). :1505--1523.
"They Look at Vulnerability and Use That to Abuse You'': Participatory Threat Modelling with Migrant Domestic Workers
.
2022. "They Look at Vulnerability and Use That to Abuse You'': Participatory Threat Modelling with Migrant Domestic Workers. 31st USENIX Security Symposium (USENIX Security 22). :323--340.
Blacklight: Scalable Defense for Neural Networks against {Query-Based} {Black-Box} Attacks
.
2022. Blacklight: Scalable Defense for Neural Networks against {Query-Based} {Black-Box} Attacks. 31st USENIX Security Symposium (USENIX Security 22). :2117--2134.
Themis: Accelerating the Detection of Route Origin Hijacking by Distinguishing Legitimate and Illegitimate {MOAS}
.
2022. Themis: Accelerating the Detection of Route Origin Hijacking by Distinguishing Legitimate and Illegitimate {MOAS}. 31st USENIX Security Symposium (USENIX Security 22). :4509--4524.
{AutoDA}: Automated Decision-based Iterative Adversarial Attacks
.
2022. {AutoDA}: Automated Decision-based Iterative Adversarial Attacks. 31st USENIX Security Symposium (USENIX Security 22). :3557--3574.
{SAPIC+}: protocol verifiers of the world, unite!
.
2022. {SAPIC+}: protocol verifiers of the world, unite!. 31st USENIX Security Symposium (USENIX Security 22). :3935--3952.
Where to Recruit for Security Development Studies: Comparing Six Software Developer Samples
.
2022. Where to Recruit for Security Development Studies: Comparing Six Software Developer Samples. 31st USENIX Security Symposium (USENIX Security 22). :4041--4058.
Ground Truth for Binary Disassembly is Not Easy
.
2022. Ground Truth for Binary Disassembly is Not Easy. 31st USENIX Security Symposium (USENIX Security 22). :2479--2495.
A {Hardware-Software} Co-design for Efficient {Intra-Enclave} Isolation
.
2022. A {Hardware-Software} Co-design for Efficient {Intra-Enclave} Isolation. 31st USENIX Security Symposium (USENIX Security 22). :3129--3145.
Poison Forensics: Traceback of Data Poisoning Attacks in Neural Networks
.
2022. Poison Forensics: Traceback of Data Poisoning Attacks in Neural Networks. 31st USENIX Security Symposium (USENIX Security 22). :3575--3592.