Wu Luo (Peking University), Xuhua Ding (Singapore Management University), Pengfei Wu (School of Computing, National University of Singapore), Xiaolei Zhang (Peking University), Qingni Shen (Peking University), Zhonghai Wu (Peking University)

We present ScriptChecker, a novel browser-based framework to effectively and efficiently restrict third-party script execution according to the host web page's needs. Different from all existing schemes functioning at the JavaScript layer, ScriptChecker holistically harnesses context separation and the browser's security monitors to enforce on-demand access controls upon tasks executing untrusted code. The host page can flexibly assign resource-access capabilities to tasks upon their creation. Reaping the benefits of the task capability approach, ScriptChecker outperforms existing techniques in security, usability and performance. We have implemented a prototype of ScriptChecker on Chrome and rigorously evaluated its security and performance with case studies and benchmarks. The experimental results show that its strong security strength and ease-of-use are attained at the cost of unnoticeable performance loss. It incurs about 0.2 microseconds overhead to mediate a DOM access, and 5% delay when loading popular JS graphics and utility libraries.

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Demo #14: In-Vehicle Communication Using Named Data Networking

Zachariah Threet (Tennessee Tech), Christos Papadopoulos (University of Memphis), Proyash Poddar (Florida International University), Alex Afanasyev (Florida International University), William Lambert (Tennessee Tech), Haley Burnell (Tennessee Tech), Sheikh Ghafoor (Tennessee Tech) and Susmit Shannigrahi (Tennessee Tech)

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Property Inference Attacks Against GANs

Junhao Zhou (Xi'an Jiaotong University), Yufei Chen (Xi'an Jiaotong University), Chao Shen (Xi'an Jiaotong University), Yang Zhang (CISPA Helmholtz Center for Information Security)

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Demo #1: Security of Multi-Sensor Fusion based Perception in...

Yulong Cao (University of Michigan), Ningfei Wang (UC, Irvine), Chaowei Xiao (Arizona State University), Dawei Yang (University of Michigan), Jin Fang (Baidu Research), Ruigang Yang (University of Michigan), Qi Alfred Chen (UC, Irvine), Mingyan Liu (University of Michigan) and Bo Li (University of Illinois at Urbana-Champaign)

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Demo #10: Hijacking Connected Vehicle Alexa Skills

Wenbo Ding (University at Buffalo), Long Cheng (Clemson University), Xianghang Mi (University of Science and Technology of China), Ziming Zhao (University at Buffalo) and Hongxin Hu (University at Buffalo)

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