Dawei Xu1,2,3, Min Wang1, Yue Lv1, Moxuan Fu2, Yi Wu4,5,*, Jian Zhao1
CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 2027-2041, 2025, DOI:10.32604/cmc.2024.058178
- 17 February 2025
Abstract Website fingerprinting (WF) attacks can reveal information about the websites users browse by de-anonymizing encrypted traffic. Traditional website fingerprinting attack models, focusing solely on a single spatial feature, are inefficient regarding training time. When confronted with the concept drift problem, they suffer from a sharp drop in attack accuracy within a short period due to their reliance on extensive, outdated training data. To address the above problems, this paper proposes a parallel website fingerprinting attack (APWF) that incorporates an attention mechanism, which consists of an attack model and a fine-tuning method. Among them, the APWF… More >
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