H
Heqing Huang
Researcher at IBM
Publications - 50
Citations - 1787
Heqing Huang is an academic researcher from IBM. The author has contributed to research in topics: Malware & Android (operating system). The author has an hindex of 17, co-authored 50 publications receiving 1323 citations. Previous affiliations of Heqing Huang include Indiana University & Kansas State University.
Papers
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Proceedings ArticleDOI
Protecting Intellectual Property of Deep Neural Networks with Watermarking
TL;DR: By extending the intrinsic generalization and memorization capabilities of deep neural networks, the models to learn specially crafted watermarks at training and activate with pre-specified predictions when observing the watermark patterns at inference, this paper generalizes the "digital watermarking'' concept from multimedia ownership verification to deep neural network (DNN) models.
Proceedings Article
Commandersong: a systematic approach for practical adversarial voice recognition
Xuejing Yuan,Yuxuan Chen,Yue Zhao,Yunhui Long,Xiaokang Liu,Kai Chen,Shengzhi Zhang,Heqing Huang,XiaoFeng Wang,Carl A. Gunter +9 more
TL;DR: Novel techniques are developed that address a key technical challenge: integrating the commands into a song in a way that can be effectively recognized by ASR through the air, in the presence of background noise, while not being detected by a human listener.
Proceedings Article
Finding unknown malice in 10 seconds: mass vetting for new threats at the Google-play scale
TL;DR: This study shows that the technique can vet an app within 10 seconds at a low false detection rate and outperformed all 54 scanners in VirusTotal in terms of detection coverage, capturing over a hundred thousand malicious apps, including over 20 likely zero-day malware and those installed millions of times.
Proceedings ArticleDOI
ViewDroid: towards obfuscation-resilient mobile application repackaging detection
TL;DR: This paper proposes ViewDroid, a user interface based approach to mobile app repackaging detection, which can detect repackaged apps at a large scale, both effectively and efficiently.
Book ChapterDOI
A Framework for Evaluating Mobile App Repackaging Detection Algorithms
TL;DR: This work proposes a framework to evaluate the obfuscation resilience of repackaging detection algorithms comprehensively, and applies this framework to conduct a comprehensive case study on AndroGuard, an Android repackaged detector proposed in Black-hat 2011.