Prazo para submissão: 20 June 2022
Data de Notificação: 01/04/2025
Editora: Elsevier
Revista: Future Generation Computer Systems
Detalhes:
Motivation and ScopeNeural Networks have demonstrated great success in many fields. However, recent studies revealed that neural networks are vulnerable to adversarial attacks. The vulnerability of neural networks, which may hinder their adoption in high-stake scenarios. Thus, understanding their vulnerability and developing robust neural networks have attracted increasing attention. To understand and accommodate the vulnerability of neural networks, various attack and defense techniques have be