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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The Nuts and Bolts of Building FlowLens

Diogo Barradas (Instituto Superior Técnico, Universidade de Lisboa)

Demo #5: Securing Heavy Vehicle Diagnostics

Jeremy Daily, David Nnaji, and Ben Ettlinger (Colorado State University)

Demo #2: Sequential Attacks on Kalman Filter-Based Forward Collision...

Yuzhe Ma, Jon Sharp, Ruizhe Wang, Earlence Fernandes, and Jerry Zhu (University of Wisconsin–Madison)

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)