Demo #10: Security of Deep Learning based Automated Lane Centering under Physical-World Attack

Takami Sato, Junjie Shen, Ningfei Wang (UC Irvine), Yunhan Jia (ByteDance), Xue Lin (Northeastern University), and Qi Alfred Chen (UC Irvine)

Automated Lane Centering (ALC) systems are convenient and widely deployed today, but also highly security and safety critical. Recently, Dirty Road Patch (DRP) attack is proposed as a state-of-the-art adversarial attack against ALC systems. We will show interactive demonstrations for the malicious road patch generation and the serious consequences.

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Low-risk Privacy-preserving Electric Vehicle Charging with Payments

Andreas Unterweger, Fabian Knirsch, Clemens Brunner and Dominik Engel (Center for Secure Energy Informatics, Salzburg University of Applied Sciences, Puch bei Hallein, Austria)

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Seonghoon Jeong, Eunji Park, Kang Uk Seo, Jeong Do Yoo, and Huy Kang Kim (Korea University)

CHANCEL: Efficient Multi-client Isolation Under Adversarial Programs

Adil Ahmad (Purdue University), Juhee Kim (Seoul National University), Jaebaek Seo (Google), Insik Shin (KAIST), Pedro Fonseca (Purdue University), Byoungyoung Lee (Seoul National University)

Practical Non-Interactive Searchable Encryption with Forward and Backward Privacy

Shi-Feng Sun (Monash University, Australia), Ron Steinfeld (Monash University, Australia), Shangqi Lai (Monash University, Australia), Xingliang Yuan (Monash University, Australia), Amin Sakzad (Monash University, Australia), Joseph Liu (Monash University, Australia), ‪Surya Nepal‬ (Data61, CSIRO, Australia), Dawu Gu (Shanghai Jiao Tong University, China)