Stain: Stealthy avenues of attacks on horizontally collaborated convolutional neural network inference and their mitigation
AA Adeyemo, JJ Sanderson, TA Odetola… - IEEE …, 2023 - ieeexplore.ieee.org
With significant potential improvement in device-to-device (D2D) communication due to
improved wireless link capacity (eg, 5G and NextG systems), a collaboration of multiple …
improved wireless link capacity (eg, 5G and NextG systems), a collaboration of multiple …
Security and privacy preservation for smart grid AMI using machine learning and cryptography
MM Badr - 2022 - search.proquest.com
In the smart grid's advanced metering infrastructure (AMI), smart meters (SMs) are deployed
at the customers' premises to report their electricity consumption readings to the electric …
at the customers' premises to report their electricity consumption readings to the electric …
Labani: Layer-based noise injection attack on convolutional neural networks
Hardware accelerator-based CNN inference improves the performance and latency but
increases the time-to-market. As a result, CNN deployment on hardware is often outsourced …
increases the time-to-market. As a result, CNN deployment on hardware is often outsourced …
FPGA implementation of a Convolutional Neural Network for image classification
T Hadjam, AM Salah, MB Nedjma… - 2022 2nd …, 2022 - ieeexplore.ieee.org
In this paper, a technique for implementing a Convolutional Neural Network (CNN) is
presented. The implementation is performed on a reconfigurable Field Programmable Gate …
presented. The implementation is performed on a reconfigurable Field Programmable Gate …
Towards Securing Edge Intelligence for Inference in Horizontal Collaborative Environments
AA Adeyemo - 2023 - search.proquest.com
With the growing demand for real-time intelligence driven by device-to-device (D2D)
communication, deploying Deep Learning (DL) applications at the network edge becomes …
communication, deploying Deep Learning (DL) applications at the network edge becomes …