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English(EN) WADE: An LSTM-Based Anomaly Detection Engine for WebAssembly Applications

WADE引擎使用LSTM检测WebAssembly应用程序攻击

研究人员开发了WADE,一种新颖的异常检测引擎,旨在识别WebAssembly应用程序中的恶意行为。WADE利用长短期记忆(LSTM)网络,通过分析函数级跟踪来学习应用程序的正常执行模式。当发生运行时偏差时,WADE会将其标记为潜在攻击,提供一种无签名的方法来检测已知和新型威胁。在对67个WebAssembly应用程序和十个漏洞类别进行的评估中,WADE实现了零假阴性,假阳性率为0.42%。 AI

影响 这项研究介绍了一种保护WebAssembly应用程序的新方法,有可能提高基于Web的软件的安全性。

排序理由 详细介绍新技术方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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WADE引擎使用LSTM检测WebAssembly应用程序攻击

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详细介绍新技术方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Ilaria Campestrini, Stefano Zanero, Engin Kirda ·

    WADE:一款基于 LSTM 的 WebAssembly 应用异常检测引擎

    arXiv:2610.31984v1 Announce Type: cross Abstract: WebAssembly (Wasm) enables near-native performance for web applications through a portable and sandboxed execution model. However, its limited runtime protection mechanisms (e.g., the lack of stack canaries and address space layou…