Static Semantics Reconstruction for Enhancing JavaScript-WebAssembly Multilingual Malware Detection

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Bibliografiske detaljer
Udgivet i:arXiv.org (Apr 19, 2024), p. n/a
Hovedforfatter: Xia, Yifan
Andre forfattere: He, Ping, Zhang, Xuhong, Liu, Peiyu, Ji, Shouling, Wang, Wenhai
Udgivet:
Cornell University Library, arXiv.org
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022 |a 2331-8422 
035 |a 2882598871 
045 0 |b d20240419 
100 1 |a Xia, Yifan 
245 1 |a Static Semantics Reconstruction for Enhancing JavaScript-WebAssembly Multilingual Malware Detection 
260 |b Cornell University Library, arXiv.org  |c Apr 19, 2024 
513 |a Working Paper 
520 3 |a The emergence of WebAssembly allows attackers to hide the malicious functionalities of JavaScript malware in cross-language interoperations, termed JavaScript-WebAssembly multilingual malware (JWMM). However, existing anti-virus solutions based on static program analysis are still limited to monolingual code. As a result, their detection effectiveness decreases significantly against JWMM. The detection of JWMM is challenging due to the complex interoperations and semantic diversity between JavaScript and WebAssembly. To bridge this gap, we present JWBinder, the first technique aimed at enhancing the static detection of JWMM. JWBinder performs a language-specific data-flow analysis to capture the cross-language interoperations and then characterizes the functionalities of JWMM through a unified high-level structure called Inter-language Program Dependency Graph. The extensive evaluation on one of the most representative real-world anti-virus platforms, VirusTotal, shows that \system effectively enhances anti-virus systems from various vendors and increases the overall successful detection rate against JWMM from 49.1\% to 86.2\%. Additionally, we assess the side effects and runtime overhead of JWBinder, corroborating its practical viability in real-world applications. 
653 |a Computer viruses 
653 |a Side effects 
653 |a Program verification (computers) 
653 |a Semantics 
653 |a Malware 
653 |a Multilingualism 
653 |a System effectiveness 
653 |a Anti-virus software 
653 |a JavaScript 
653 |a Data flow analysis 
700 1 |a He, Ping 
700 1 |a Zhang, Xuhong 
700 1 |a Liu, Peiyu 
700 1 |a Ji, Shouling 
700 1 |a Wang, Wenhai 
773 0 |t arXiv.org  |g (Apr 19, 2024), p. n/a 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/2882598871/abstract/embedded/ZKJTFFSVAI7CB62C?source=fedsrch 
856 4 0 |3 Full text outside of ProQuest  |u http://arxiv.org/abs/2310.17304