// Security

ArXiv Preprint

AAOS Privacy

Investigating the privacy implications of Android Automotive OS (AAOS) in vehicles. We developed PriDrive, to perform static, dynamic, and network traffic inspection to evaluate the data collected by OEMs and compare it against their privacy policies. Contribution: privacy policy analyzer.

1st Cyber Security in Cars Workshop (CSCS) at CCS

AV Safety/Security

A survey paper examining security and safety challenges in autonomous vehicles (AVs). E.g., AV vulnerabilities, including surveillance risks, sensor system reliability, adversarial attacks, and regulatory concerns. Contribution: writing for surveillance and environmental safety risks.

32nd USENIX Security Symposium (2023)

Eye-Shield

A novel defense system against shoulder surfing attacks on mobile devices. We designed Eye-Shield, a real-time software that makes on-screen content readable to the user but appear blurry to onlookers. Contribution: lead author.

32nd USENIX Security Symposium (2023)

Face Obfuscation Fairness

Investigating the demographic fairness of anti face recognition systems. We analyze how these metric embedding networks may exhibit disparities across different demographic groups. Contribution: coded, implemented, and tested theoretical framework proposed by lead author.

21st Symposium Privacy Enhancing Technologies (2021)

Face-Off

Protecting user privacy by preventing face recognition. Face-Off introduces perturbations to face images, making them unrecognizable to commercial face recognition models. Contribution: coding, evaluation, and deployment, creating one of the first anti face recognition systems.

ArXiv Preprint

Hierarchical Robustness

A case study and evaluation on how deep neural networks (DNNs) are highly effective but vulnerable to adversarial inputs. Contribution: implemented hierarchical classification approach that leverages invariant features to enhance adversarial robustness without compromising accuracy.