Publications

EchoGuard: Continuous Ultrasound-Based Human Presence Verification for AI Agent Detections

Yizhu Wen^{*equal contribution}, Dharani Nadendla^{*equal contribution}, Shirui Cao, Renzhi Hao, Dong Li, and Hanqing Guo

In Proceedings of the 9th ACM/IEEE Workshop on Security and Privacy in Edge Computing (EdgeSP 2026), co-located with the ACM/IEEE Symposium on Edge Computing (SEC 2026), October 2026.

Uses ultrasound sensing to continuously verify that a real person, rather than an AI agent, is present at a device.

@inproceedings{wen2026echoguard,
  title     = {{EchoGuard}: Continuous Ultrasound-Based Human Presence
               Verification for {AI} Agent Detections},
  author    = {Wen, Yizhu and Nadendla, Dharani and Cao, Shirui and
               Hao, Renzhi and Li, Dong and Guo, Hanqing},
  booktitle = {Proceedings of the 9th ACM/IEEE Workshop on Security
               and Privacy in Edge Computing (EdgeSP)},
  year      = {2026}
}

Ultrasound Watermark: Real-Time Acoustic Watermarking against Voice Scams on Smartphones

Renzhi Hao, Shirui Cao, Yizhu Wen, Rishav Gupta, Dharani Nadendla, Mehran Kafai, Hanqing Guo, and Dong Li

In Proceedings of the 9th ACM/IEEE Workshop on Security and Privacy in Edge Computing (EdgeSP 2026), co-located with the ACM/IEEE Symposium on Edge Computing (SEC 2026), October 2026.

Embeds real-time acoustic watermarks to help protect smartphone users from voice scams.

@inproceedings{hao2026ultrasound,
  title     = {Ultrasound Watermark: Real-Time Acoustic Watermarking
               against Voice Scams on Smartphones},
  author    = {Hao, Renzhi and Cao, Shirui and Wen, Yizhu and
               Gupta, Rishav and Nadendla, Dharani and Kafai, Mehran and
               Guo, Hanqing and Li, Dong},
  booktitle = {Proceedings of the 9th ACM/IEEE Workshop on Security
               and Privacy in Edge Computing (EdgeSP)},
  year      = {2026}
}

MASCOT: Analyzing Malware Evolution Through a Well-Curated Source Code Dataset

Bojing Li, Duo Zhong, Dharani Nadendla, Gabriel Terceros, Prajna Bhandary, Raguvir S, and Charles Nicholas

arXiv preprint arXiv:2512.00741, November 2025.

A manually reviewed dataset of 6,032 malware source-code samples. It is used to study the size, quality, security, and dependencies of modern malware, and to trace how code reuse drives malware lineages.

@article{li2025mascot,
  title   = {{MASCOT}: Analyzing Malware Evolution Through a
             Well-Curated Source Code Dataset},
  author  = {Li, Bojing and Zhong, Duo and Nadendla, Dharani and
             Terceros, Gabriel and Bhandary, Prajna and S, Raguvir and
             Nicholas, Charles},
  journal = {arXiv preprint arXiv:2512.00741},
  year    = {2025}
}

Ultrasound Watermark: Real-Time Acoustic Watermarking against Voice Scams on Smartphones

Renzhi Hao, Shirui Cao, Yizhu Wen, Rishav Gupta, Dharani Nadendla, Mehran Kafai, Hanqing Guo, and Dong Li

Submitted to ACM MobiCom 2027.