Junjie Shen

Orcid: 0000-0001-7944-4445

Affiliations:
  • University of California, Irvine, CA, USA


According to our database1, Junjie Shen authored at least 25 papers between 2017 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

Online presence:

On csauthors.net:

Bibliography

2023
Anomaly Detection Against GPS Spoofing Attacks on Connected and Autonomous Vehicles Using Learning From Demonstration.
IEEE Trans. Intell. Transp. Syst., September, 2023

Detecting Data Spoofing in Connected Vehicle based Intelligent Traffic Signal Control using Infrastructure-Side Sensors and Traffic Invariants.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2023

Lateral-Direction Localization Attack in High-Level Autonomous Driving: Domain-Specific Defense Opportunity via Lane Detection.
IROS, 2023

2022
Security Challenges and Defense Opportunities of Connected and Autonomous Vehicle Systems in the Physical World
PhD thesis, 2022

SoK: On the Semantic AI Security in Autonomous Driving.
CoRR, 2022

Too Afraid to Drive: Systematic Discovery of Semantic DoS Vulnerability in Autonomous Driving Planning under Physical-World Attacks.
Proceedings of the 29th Annual Network and Distributed System Security Symposium, 2022

Play the Imitation Game: Model Extraction Attack against Autonomous Driving Localization.
Proceedings of the Annual Computer Security Applications Conference, 2022

2021
Dirty Road Can Attack: Security of Deep Learning based Automated Lane Centering under Physical-World Attack.
Proceedings of the 30th USENIX Security Symposium, 2021

Demo: ROI Attacks on Traffic Light Detection in High-Level Autonomous Driving.
Proceedings of the IEEE Security and Privacy Workshops, 2021

Demo: Security of Deep Learning based Automated Lane Centering under Physical-World Attack.
Proceedings of the IEEE Security and Privacy Workshops, 2021

Demo: Attacking Multi-Sensor Fusion based Localization in High-Level Autonomous Driving.
Proceedings of the IEEE Security and Privacy Workshops, 2021

End-to-end Uncertainty-based Mitigation of Adversarial Attacks to Automated Lane Centering.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2021

2020
Hold Tight and Never Let Go: Security of Deep Learning based Automated Lane Centering under Physical-World Attack.
CoRR, 2020

Drift with Devil: Security of Multi-Sensor Fusion based Localization in High-Level Autonomous Driving under GPS Spoofing (Extended Version).
CoRR, 2020

Security of Deep Learning based Lane Keeping System under Physical-World Adversarial Attack.
CoRR, 2020

Exploring Convolution Neural Network for Branch Prediction.
IEEE Access, 2020

Drift with Devil: Security of Multi-Sensor Fusion based Localization in High-Level Autonomous Driving under GPS Spoofing.
Proceedings of the 29th USENIX Security Symposium, 2020

A comprehensive study of autonomous vehicle bugs.
Proceedings of the ICSE '20: 42nd International Conference on Software Engineering, Seoul, South Korea, 27 June, 2020

Fooling Detection Alone is Not Enough: Adversarial Attack against Multiple Object Tracking.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
Fooling Detection Alone is Not Enough: First Adversarial Attack against Multiple Object Tracking.
CoRR, 2019

LXDs: Towards Isolation of Kernel Subsystems.
Proceedings of the 2019 USENIX Annual Technical Conference, 2019

Combining Prefetch Control and Cache Partitioning to Improve Multicore Performance.
Proceedings of the 2019 IEEE International Parallel and Distributed Processing Symposium, 2019

2018
A Study on Deep Belief Net for Branch Prediction.
IEEE Access, 2018

New Opportunities for Compilers in Computer Security.
Proceedings of the Languages and Compilers for Parallel Computing, 2018

2017
CAMFAS: A Compiler Approach to Mitigate Fault Attacks via Enhanced SIMDization.
IACR Cryptol. ePrint Arch., 2017


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