Published in 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2024
This paper proposes an extensible multimodal Bayesian network architecture that efficiently integrates deep neural networks with clinical metadata for skin disease diagnosis, achieving 19.3% accuracy improvement over baseline methods.
Published in 27th Information Security Conference (ISC), 2024
This paper is about INCISE, a symbolic model checking algorithm that efficiently searches for secure configuration spaces, enabling system engineers to quickly verify configuration security, and successfully demonstrated its effectiveness on cellular network emergency call systems.
Published in 61th ACM/IEEE Design Automation Conference (DAC), 2024
This paper demonstrates the vulnerability of HPNN-style logic locking schemes on deep neural networks by proposing a systematic I/O attack that combines algebraic and learning-based approaches to efficiently extract protected parameters.
Published in 60th ACM/IEEE Design Automation Conference (DAC), 2023
This paper is about SE3, an efficient sequential equivalence checker without assumption on cycle-accuracy, latch mapping, or I/O interface of the checked circuits.
Published in IEEE 20th International Symposium on Biomedical Imaging (ISBI), 2023
This paper is about an automatic skin disease diagnosis architecture that combines deep neural networks as nodes into Bayesian networks, which combines human knowledge with the perceptual results of deep learning tools.
Published in Design, Automation & Test in Europe Conference & Exhibition (DATE), 2023
This paper is about ObfusLock, a novel logic locking scheme that simultaneously achieves I/O attack resilience, structural attack resilience, locking efficiency and protection diversity.