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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POSEIDON: Privacy-Preserving Federated Neural Network Learning

Sinem Sav (EPFL), Apostolos Pyrgelis (EPFL), Juan Ramón Troncoso-Pastoriza (EPFL), David Froelicher (EPFL), Jean-Philippe Bossuat (EPFL), Joao Sa Sousa (EPFL), Jean-Pierre Hubaux (EPFL)

Drivers and Passengers Maybe the Weakest Link in the...

Aiping Xiong (Pennsylvania State University), Zekun Cai (Pennsylvania State University) and Tianhao Wang (University of Virginia)

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)

Physical Layer Data Manipulation Attacks on the CAN Bus

Abdullah Zubair Mohammed (Virginia Tech), Yanmao Man (University of Arizona), Ryan Gerdes (Virginia Tech), Ming Li (University of Arizona) and Z. Berkay Celik (Purdue University)