This paper proposes a hardware Trojan designed to attack a crucial component of FPGA-based CNN accelerators: the reconfigurable interconnection network. Specifically, the hardware Trojan alters the data paths during activation, resulting in incorrect connections in the arithmetic circuit and consequently ...
Hardware Trojan in FPGA CNN Accelerator Maliciously manipulating prediction results of Convolutional Neural Network (CNN) is a severe security threat. Previous works studied this threat from the ... Y Jing,H Yu,X Li - IEEE Asian Test Symposium 被引量: 0发表: 2018年 Live demonstration: An FPG...
Energy-efficient multimodal zero-shot learning using in-memory reservoir computing To achieve an advanced neuromorphic computing system with brain-like energy efficiency and generalization capabilities, we propose a hardware–software co-design of in-memory reservoir computing. This co-design integrates a...
In this brief, we design an FPGA-based accelerator for general matrix-matrix multiplication (GeMM) to improve the efficiency of convolutional layers of Shufflenet, an efficient convnet architecture. Experimental results show significant performance improvements against the state-of-the-art FPGA-based ...
a hardware Trojan is investigated that targets the reconfigurable interconnection network of CNN accelerators, resulting in incorrect computations and a decrease in inference accuracy with minimal hardware cost. The experiments demonstrated that it could lead to accuracy degradation from 8.93% to 86.20%. ...
The following pic is cropped from the HDMI output of FPGA. The white rectangle is draw by FPGA. Move a Mnist digit picture into the rectangle, or draw a digit by hand using a Paint software. The printed digit under the rectangle is the the classified result. ...
Xilinx and Motovis announced today that the two companies are collaborating on a solution that pairs the Xilinx Automotive (XA) Zynq® system-on-chip (SoC) platform and Motovis’ convolutional neural network (CNN) IP to the automotive market, specifica
One possible solution to this problem comes from the development of customized hardware designed to perform the run-time computations of a CNN. Due to the low power consumption and high flexibility seen in Field Programmable Gate Arrays (FPGAs), these devices are a popular choice for realizing ...
A Survey of Hardware Trojan Taxonomy and Detection Editor's note:Today's integrated circuits are vulnerable to hardware Trojans, which are malicious alterations to the circuit, either during design or fabri... M Tehranipoor,F Koushanfar - 《IEEE Design & Test of Computers》 被引量: 790发表:...
A CNN Hardware Accelerator in FPGA for Stacked Hourglass NetworkStaked hourglass network is a widely used deep neural network model for body pose estimation. The essence of this model can be roughly considered as a combination of Deep Convolutional Neural......