Backdoor attacks and defenses targeting multi-domain ai models: A comprehensive review
Since the emergence of security concerns in artificial intelligence (AI), there has been
significant attention devoted to the examination of backdoor attacks. Attackers can utilize …
significant attention devoted to the examination of backdoor attacks. Attackers can utilize …
Distributed computing in multi-agent systems: a survey of decentralized machine learning approaches
At present, there is a pressing need for data scientists and academic researchers to devise
advanced machine learning and artificial intelligence-driven systems that can effectively …
advanced machine learning and artificial intelligence-driven systems that can effectively …
3d adversarial attacks beyond point cloud
Recently, 3D deep learning models have been shown to be susceptible to adversarial
attacks like their 2D counterparts. Most of the state-of-the-art (SOTA) 3D adversarial attacks …
attacks like their 2D counterparts. Most of the state-of-the-art (SOTA) 3D adversarial attacks …
AI for water
FA Batarseh, A Kulkarni - Computer, 2023 - computer.org
AI for Water Toggle navigation IEEE Computer Society Digital Library Jobs Tech News
Resource Center Press Room Advertising About Us IEEE IEEE Computer Society IEEE …
Resource Center Press Room Advertising About Us IEEE IEEE Computer Society IEEE …
Learning disentangled features for person re-identification under clothes changing
Clothes changing is one of the challenges in person re-identification (ReID), since clothes
provide remarkable and reliable information for decision, especially when the resolution of …
provide remarkable and reliable information for decision, especially when the resolution of …
Meta In-Context Learning: Harnessing Large Language Models for Electrical Data Classification
The evolution of communication technology has driven the demand for intelligent power
grids and data analysis in power systems. However, obtaining and annotating electrical data …
grids and data analysis in power systems. However, obtaining and annotating electrical data …
On and off the manifold: Generation and Detection of adversarial attacks in IIoT networks
Abstract Network Intrusion Detection Systems (NIDS), which play a crucial role in defending
Industrial Internet of Things (IIoT) networks, often utilize Deep Neural Networks (DNN) for …
Industrial Internet of Things (IIoT) networks, often utilize Deep Neural Networks (DNN) for …
Defending against Poisoning Attacks in Aerial Image Semantic Segmentation with Robust Invariant Feature Enhancement
Z Wang, B Wang, C Zhang, Y Liu, J Guo - Remote Sensing, 2023 - mdpi.com
The outstanding performance of deep neural networks (DNNs) in multiple computer vision in
recent years has promoted its widespread use in aerial image semantic segmentation …
recent years has promoted its widespread use in aerial image semantic segmentation …
A Secure federated learning framework based on autoencoder and Long Short-Term Memory with generalized robust loss function for detection and prevention of …
P Singh - Biomedical Signal Processing and Control, 2025 - Elsevier
In this research, a federated learning-based poisoning attack recognition and prevention
framework has been developed. Initially, the required data to perform data poison attack …
framework has been developed. Initially, the required data to perform data poison attack …
Hiding Backdoors within Event Sequence Data via Poisoning Attacks
A Ermilova, E Kovtun, D Berestnev… - arXiv preprint arXiv …, 2023 - arxiv.org
The financial industry relies on deep learning models for making important decisions. This
adoption brings new danger, as deep black-box models are known to be vulnerable to …
adoption brings new danger, as deep black-box models are known to be vulnerable to …