Consistent Valid Physically-Realizable Adversarial Attack Against Crowd-Flow Prediction Models

Consistent Valid Physically-Realizable Adversarial Attack Against Crowd-Flow Prediction Models

<p dir="ltr">Recent works have shown that deep learning (DL) models can effectively learn city-wide crowd-flow patterns, which can be used for more effective urban planning and smart city management. However, DL models have been known to perform poorly on inconspicuous adversarial pe...

Full description

Saved in:
Bibliographic Details
Main Author: Hassan Ali (3348749) (author)
Other Authors: Muhammad Atif Butt (10849980) (author), Fethi Filali (12646471) (author), Ala Al-Fuqaha (4434340) (author), Junaid Qadir (16494902) (author)
Published: 2023
Subjects:
Information and computing sciences
Artificial intelligence
Cybersecurity and privacy
Data management and data science
Machine learning
Deep neural networks
CFP
adversarial ML
Perturbation methods
Standards
Adaptation models
Computer architecture
Analytical models
History
Data models
Tags: Add Tag
No Tags, Be the first to tag this record!
Be the first to leave a comment!
You must be logged in first

Similar Items