Search Results for author: Xiaolin Xu

Found 10 papers, 4 papers with code

NNSplitter: An Active Defense Solution to DNN Model via Automated Weight Obfuscation

no code implementations28 Apr 2023 Tong Zhou, Yukui Luo, Shaolei Ren, Xiaolin Xu

As a type of valuable intellectual property (IP), deep neural network (DNN) models have been protected by techniques like watermarking.

MetaLDC: Meta Learning of Low-Dimensional Computing Classifiers for Fast On-Device Adaption

1 code implementation23 Feb 2023 Yejia Liu, Shijin Duan, Xiaolin Xu, Shaolei Ren

Fast model updates for unseen tasks on intelligent edge devices are crucial but also challenging due to the limited computational power.


SDFE-LV: A Large-Scale, Multi-Source, and Unconstrained Database for Spotting Dynamic Facial Expressions in Long Videos

no code implementations18 Sep 2022 Xiaolin Xu, Yuan Zong, Wenming Zheng, Yang Li, Chuangao Tang, Xingxun Jiang, Haolin Jiang

In this paper, we present a large-scale, multi-source, and unconstrained database called SDFE-LV for spotting the onset and offset frames of a complete dynamic facial expression from long videos, which is known as the topic of dynamic facial expression spotting (DFES) and a vital prior step for lots of facial expression analysis tasks.

ObfuNAS: A Neural Architecture Search-based DNN Obfuscation Approach

1 code implementation17 Aug 2022 Tong Zhou, Shaolei Ren, Xiaolin Xu

Nonetheless, we observe that, with only extracting an obfuscated DNN architecture, the adversary can still retrain a substitute model with high performance (e. g., accuracy), rendering the obfuscation techniques ineffective.

Neural Architecture Search

LeHDC: Learning-Based Hyperdimensional Computing Classifier

1 code implementation18 Mar 2022 Shijin Duan, Yejia Liu, Shaolei Ren, Xiaolin Xu

Thanks to the tiny storage and efficient execution, hyperdimensional Computing (HDC) is emerging as a lightweight learning framework on resource-constrained hardware.

A Brain-Inspired Low-Dimensional Computing Classifier for Inference on Tiny Devices

1 code implementation9 Mar 2022 Shijin Duan, Xiaolin Xu, Shaolei Ren

Nonetheless, they have two fundamental drawbacks, heuristic training process and ultra-high dimension, which result in sub-optimal inference accuracy and large model sizes beyond the capability of tiny devices with stringent resource constraints.

Deep-Dup: An Adversarial Weight Duplication Attack Framework to Crush Deep Neural Network in Multi-Tenant FPGA

no code implementations5 Nov 2020 Adnan Siraj Rakin, Yukui Luo, Xiaolin Xu, Deliang Fan

Specifically, she can aggressively overload the shared power distribution system of FPGA with malicious power-plundering circuits, achieving adversarial weight duplication (AWD) hardware attack that duplicates certain DNN weight packages during data transmission between off-chip memory and on-chip buffer, to hijack the DNN function of the victim tenant.

Adversarial Attack Image Classification +2

EOP: An Encryption-Obfuscation Solution for Protecting PCBs Against Tampering and Reverse Engineering

no code implementations20 Apr 2019 Zimu Guo, Xiaolin Xu, Mark M. Tehranipoor, Domenic Forte

These modules guarantee the stream cipher is correctly synchronized and free from tampering.

Cryptography and Security

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