Zihao Jin (Microsoft Research and Tsinghua University), Shuo Chen (Microsoft Research), Yang Chen (Microsoft Research), Haixin Duan (Tsinghua University and Quancheng Laboratory), Jianjun Chen (Tsinghua University and Zhongguancun Laboratory), Jianping Wu (Tsinghua University)

The Electron platform represents a paradigm to develop modern desktop apps using HTML and JavaScript. Microsoft Teams, Visual Studio Code and other flagship products are examples of Electron apps. This new paradigm inherits the security challenges in web programming into the desktop-app realm, thus opens a new way for local-machine exploitation. We conducted a security study about real-world Electron apps, and discovered many vulnerabilities that are now confirmed by the app vendors. The conventional wisdom is to view these bugs as *sanitization errors*. Accordingly, secure programming requires programmers to explicitly enumerate all kinds of unexpected inputs to sanitize. We believe that secure programming should focus on specifying programmers' intentions as opposed to their non-intentions. We introduce a concept called *DOM-tree type*, which expresses the set of DOM trees that an app expects to see during execution, so an exploit will be caught as a type violation. With insights into the HTML standard and the Chromium engine, we build the DOM-tree type mechanism into the Electron platform. The evaluations show that the methodology is practical, and it secures all vulnerable apps that we found in the study.

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Improving In-vehicle Networks Intrusion Detection Using On-Device Transfer Learning

Sampath Rajapaksha (Robert Gordon University), Harsha Kalutarage (Robert Gordon University), M.Omar Al-Kadri (Birmingham City University), Andrei Petrovski (Robert Gordon University), Garikayi Madzudzo (Horiba Mira Ltd)

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MetaWave: Attacking mmWave Sensing with Meta-material-enhanced Tags

Xingyu Chen (University of Colorado Denver), Zhengxiong Li (University of Colorado Denver), Baicheng Chen (University of California San Diego), Yi Zhu (SUNY at Buffalo), Chris Xiaoxuan Lu (University of Edinburgh), Zhengyu Peng (Aptiv), Feng Lin (Zhejiang University), Wenyao Xu (SUNY Buffalo), Kui Ren (Zhejiang University), Chunming Qiao (SUNY at Buffalo)

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RAI2: Responsible Identity Audit Governing the Artificial Intelligence

Tian Dong (Shanghai Jiao Tong University), Shaofeng Li (Shanghai Jiao Tong University), Guoxing Chen (Shanghai Jiao Tong University), Minhui Xue (CSIRO's Data61), Haojin Zhu (Shanghai Jiao Tong University), Zhen Liu (Shanghai Jiao Tong University)

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