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publications
Day-ahead Coordinated Scheduling of Hydro and Wind Power Generation System Considering Uncertainties
Published in IEEE Transactions on Industry Applications, 2019
This paper is about day-ahead scheduling of hydro and wind power generation system.
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Bit2RNG: Leveraging Bad-page Initialized Table with Bit-error Insertion for True Random Number Generation in Commodity Flash Memory
Published in IEEE International Symposium on Hardware Oriented Security and Trust (HOST), 2020
This paper is about hardware-based random number generator.
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Security and Privacy in the Emerging Cyber-Physical World: A Survey
Published in IEEE Communications Surveys & Tutorials (IEEE COMST), 2021
This paper is about systemization of cyber-physical attacks.
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Towards Automated Computational Auditing of mHealth Security and Privacy Regulations
Published in ACM Conference on Computer and Communications Security (CCS), 2021
This paper is about automatic auditing of privacy regulations.
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PowerTouch: A Security Objective-Guided Automation Framework for Generating Wired Ghost Touch Attacks on Touchscreens
Published in IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2022
This paper is about automatic generation of GhostTouch attacks against capacitive touch screen.
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When Evil Calls: Targeted Adversarial Voice over IP Network
Published in ACM Conference on Computer and Communications Security (CCS), 2022
This paper is about generating and deliverying adversarial audio examples over IP network.
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HeatDeCam: Detecting Hidden Spy Cameras via Thermal Emissions
Published in ACM Conference on Computer and Communications Security (CCS), 2022
This paper is about using machine learning to detect hidden spy cameras within thermal images.
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PolyRhythm: Adaptive Tuning of a Multi-Channel Attack Template for Timing Interference
Published in IEEE Real-Time Systems Symposium (RTSS), 2022
This paper is about generting resource contention attack with primitives across multiple architectural and kernel-based channels.
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SlowLiDAR: Increasing the Latency of LiDAR-Based Detection Using Adversarial Examples
Published in IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
This paper is about delaying LiDAR processing via adversarial purterbations on point clouds.
CodeIPPrompt: Intellectual Property Infringement Assessment of Code Language Models
Published in International Conference on Machine Learning, 2023
This paper is about measuring potential intellectual property infringement of code generation models.
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SMACK: Semantically Meaningful Adversarial Audio Attack
Published in USENIX Security Symposium, 2023
This paper is about generating semantic adversarial audio examples by perturbing prosody attributes.
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XCheck: Verifying Integrity of 3D Printed Patient-Specific Devices via Computing Tomography
Published in USENIX Security Symposium, 2023
This paper is about a defense-in-depth approach for medical 3D printing, leveraging medical CT and computational graphic techniques.
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AntiFake: Using Adversarial Audio to Prevent Unauthorized Speech Synthesis
Published in ACM Conference on Computer and Communications Security (CCS), 2023
This paper is about a proactive defense against unauthorized speech synthesis (DeepFake) attacks.
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Please Tell Me More: Privacy Impact of Explainability through the Lens of Membership Inference Attack
Published in IEEE Symposium on Security and Privacy (SP), 2024
This paper is about membership inference attacks with the aid of XAI techniques.
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Don’t Listen To Me: Understanding and Exploring Jailbreak Prompts of Large Language Models
Published in USENIX Security Symposium, 2024
This paper is about investigating LLM jailbreak threats, from the perspective of empirical evaluation and automatic generation.
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PhySense: Defending Physically Realizable Attacks for Autonomous Systems via Consistency Reasoning
Published in ACM Conference on Computer and Communications Security (CCS), 2024
This paper is about our defense-in-depth system that safeguards autonomous systems against physical realizable adversarial attacks. The defense relies on robust physical rules and holistic reasoning on the perceived scene.
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talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
TA for SP22 CSE 569S: Recent Advances in Computer Security and Privacy
Graduate course, Washington University in St. Louis, Department of Computer Science and Engineering, 2022
Designed a lab module about physically realizable adversarial machine learning attack against autonomous vehicles (AVs). The students were guided to train and generate adversarial patches to be physically attached on stop sign and human body, such that they would not be recognized by Yolo recognition algorithm equipped on AVs. Real world experiments were conducted on a set-up Adeept Rasptank car in a simulated city.