3 papers
cs.CR2026
Spike-PTSD: A Bio-Plausible Adversarial Example Attack on Spiking Neural Networks via PTSD-Inspired Spike Scaling
Lingxin Jin, Wei Jiang, Maregu Assefa Habtie +5
Spiking Neural Networks (SNNs) are energy-efficient and biologically plausible, ideal for embedded and security-critical systems, yet their adversarial robustness remains open. Exi…
cs.CR2024
Data Poisoning-based Backdoor Attack Framework against Supervised Learning Rules of Spiking Neural Networks
Lingxin Jin, Meiyu Lin, Wei Jiang +1
Spiking Neural Networks (SNNs), the third generation neural networks, are known for their low energy consumption and high robustness. SNNs are developing rapidly and can compete wi…
cs.CR2024
A Survey of Trojan Attacks and Defenses to Deep Neural Networks
Lingxin Jin, Xianyu Wen, Wei Jiang +1
Deep Neural Networks (DNNs) have found extensive applications in safety-critical artificial intelligence systems, such as autonomous driving and facial recognition systems. However…