TextCheater: A Query-Efficient Textual Adversarial Attack in the Hard-Label Setting

• Published in: IEEE transactions on dependable and secure computing Vol. 21; no. 4; pp. 3901 - 3916
• Main Authors: Peng, Hao, Guo, Shixin, Zhao, Dandan, Zhang, Xuhong, Han, Jianmin, Ji, Shouling, Yang, Xing, Zhong, Ming
• Format: Journal Article
• Language: English
• Published: Washington IEEE 01.07.2024; IEEE Computer Society
• Subjects: Adversarial examples; Data mining; deep learning security; Heuristic methods; Internet; Labels; Natural language processing; Optimization; Perturbation methods; Queries; Query processing; Search methods; Search problems; Search process; Semantics; Sentiment analysis; Tabu search; Task analysis; textual adversarial attack

Designing a query-efficient attack strategy to generate high-quality adversarial examples under the hard-label black-box setting is a fundamental yet challenging problem, especially in natural language processing (NLP). The process of searching for adversarial examples has many uncertainties (e.g.,...