Understanding and Mitigating the Security Risks of Voice-Controlled Third-Party Skills on Amazon Alexa and Google Home

no code implementations • 3 May 2018 • Nan Zhang, Xianghang Mi, Xuan Feng, Xiao-Feng Wang, Yuan Tian, Feng Qian

The significance of our findings have already been acknowledged by Amazon and Google, and further evidenced by the risky skills discovered on Alexa and Google markets by the new detection systems we built.

Cryptography and Security

Understanding IoT Security Through the Data Crystal Ball: Where We Are Now and Where We Are Going to Be

no code implementations • 28 Mar 2017 • Nan Zhang, Soteris Demetriou, Xianghang Mi, Wenrui Diao, Kan Yuan, Peiyuan Zong, Feng Qian, Xiao-Feng Wang, Kai Chen, Yuan Tian, Carl A. Gunter, Kehuan Zhang, Patrick Tague, Yue-Hsun Lin

We systemize this process, by proposing a taxonomy for the IoT ecosystem and organizing IoT security into five problem areas.

Cryptography and Security

SpamDam: Towards Privacy-Preserving and Adversary-Resistant SMS Spam Detection

no code implementations • 15 Apr 2024 • Yekai Li, Rufan Zhang, Wenxin Rong, Xianghang Mi

In this study, we introduce SpamDam, a SMS spam detection framework designed to overcome key challenges in detecting and understanding SMS spam, such as the lack of public SMS spam datasets, increasing privacy concerns of collecting SMS data, and the need for adversary-resistant detection models.

Adversarial Robustness Backdoor Attack +3