Suchergebnisse - Malicious JavaScript detection

Taylor–HHO algorithm: A hybrid optimization algorithm with deep long short‐term for malicious JavaScript detection von Alex, Scaria, Dhiliphan Rajkumar, T.

“… The malicious script, like, JavaScript, is a major threat to computer networks in terms of network security …”
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ZipAST: Enhancing malicious JavaScript detection with sequence compression von Chen, Zixian, Wang, Weiping, Qin, Yan, Zhang, Shigeng

“… With the advancements in deep learning technologies, deep learning networks have shown the ability to automatically learn strong feature representations from malicious JavaScript …”
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JSContana: Malicious JavaScript detection using adaptable context analysis and key feature extraction von Huang, Yunhua, Li, Tao, Zhang, Lijia, Li, Beibei, Liu, Xiaojie

“… Although malicious JavaScript detection methods are becoming increasingly effective, the existing methods based on feature matching or static word embeddings are difficult to detect different …”
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JStrong: Malicious JavaScript detection based on code semantic representation and graph neural network von Fang, Yong, Huang, Chaoyi, Zeng, Minchuan, Zhao, Zhiying, Huang, Cheng

“… However, the attacker uses the dynamic characteristics of the JavaScript language to embed malicious code into web pages to achieve the purpose of smuggling, redirection, and so on …”
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Research on Malicious JavaScript Detection Technology Based on LSTM von Fang, Yong, Huang, Cheng, Liu, Liang, Xue, Min

“… By analyzing the existing researches on malicious JavaScript detection, a malicious JavaScript detection model based on LSTM …”
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Malicious JavaScript Detection Based on Bidirectional LSTM Model von Song, Xuyan, Chen, Chen, Cui, Baojiang, Fu, Junsong

“… To solve this problem, many learning-based methods for malicious JavaScript detection are being explored …”
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Detecting malicious JavaScript code based on semantic analysis von Fang, Yong, Huang, Cheng, Su, Yu, Qiu, Yaoyao

“… However, attackers use the dynamics feature of JavaScript language to embed malicious code into web pages for the purpose of drive-by-download, redirection, etc …”
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Spider bird swarm algorithm with deep belief network for malicious JavaScript detection von Alex, Scaria, Dhiliphan Rajkumar, T

“… ) algorithm for malicious JavaScript detection. The proposed S-BSA is designed by the integration of Spider Monkey Optimization (SMO …”
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Detection of Obfuscated Malicious JavaScript Code von Alazab, Ammar, Khraisat, Ansam, Alazab, Moutaz, Singh, Sarabjot

“… To secure Internet users, an adequate intrusion-detection system (IDS) for malicious JavaScript must be developed …”
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JACLNet:Application of adaptive code length network in JavaScript malicious code detection von Zhang, Zhining, Wan, Liang, Chu, Kun, Li, Shusheng, Wei, Haodong, Tang, Lu

“… Currently, JavaScript malicious code detection methods are becoming more and more …”
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TransAST: A Machine Translation-Based Approach for Obfuscated Malicious JavaScript Detection von Qin, Yan, Wang, Weiping, Chen, Zixian, Song, Hong, Zhang, Shigeng

“… As an essential part of the website, JavaScript greatly enriches its functions. At the same time, JavaScript has become the most common attack payload on malicious website …”
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ScriptNet: Neural Static Analysis for Malicious JavaScript Detection von Stokes, Jack W., Agrawal, Rakshit, McDonald, Geoff, Hausknecht, Matthew

“… For internet-scale processing, static analysis offers substantial computing efficiencies. We propose the ScriptNet system for neural malicious JavaScript detection which is based on static analysis …”
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Detection of malicious javascript on an imbalanced dataset von Phung, Ngoc Minh, Mimura, Mamoru

“… In order to be able to detect new malicious JavaScript with low cost, methods with machine learning techniques have been proposed and gave positive results …”
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An Approach for Malicious JavaScript Detection Using Adaptive Taylor Harris Hawks Optimization-Based Deep Convolutional Neural Network von Alex, Scaria, T, Dhiliphan Rajkumar

“… This paper devises a novel technique for detecting malicious JavaScript. Here, JavaScript codes are fed to the feature extraction phase for extracting the noteworthy …”
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Detecting Malicious JavaScript Using Structure-Based Analysis of Graph Representation von Rozi, Muhammad Fakhrur, Ban, Tao, Ozawa, Seiichi, Yamada, Akira, Takahashi, Takeshi, Kim, Sangwook, Inoue, Daisuke

“… Malicious JavaScript code in web applications poses a significant threat as cyber attackers exploit it to perform various malicious activities …”
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A machine learning approach to detection of JavaScript-based attacks using AST features and paragraph vectors von Ndichu, Samuel, Kim, Sangwook, Ozawa, Seiichi, Misu, Takeshi, Makishima, Kazuo

“… Most of these websites use JavaScript (JS) to create dynamic content. The exploitation of vulnerabilities in servers, plugins, and other third-party systems enables the insertion of malicious codes into website …”
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Malicious JavaScript Code Detection Based on Hybrid Analysis von He, Xincheng, Xu, Lei, Cha, Chunliu

“… However, since the heavy use of obfuscation techniques, many methods no longer apply to malicious JavaScript code detection, and it has been a huge challenge to de-obfuscate obfuscated malicious Java …”
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Adaptive Spider Bird Swarm Algorithm-Based Deep Recurrent Neural Network for Malicious JavaScript Detection Using Box-Cox Transformation von Alex, Scaria, Rajkumar, T Dhiliphan

“… ) is proposed for detecting the malicious JavaScript codes in web applications. However, the proposed adaptive SBSA is designed by integrating the adaptive concept with the bird swarm algorithm (BSA …”
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Detecting Malicious Javascript in PDF through Document Instrumentation von Daiping Liu, Haining Wang, Stavrou, Angelos

“… In this paper, we propose a context-aware approach for detection and confinement of malicious Javascript in PDF …”
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Malicious JavaScript Detection by Features Extraction von Gerardo Canfora, Francesco Mercaldo, Corrado Aaron Visaggio

“… Existing techniques for detecting malicious JavaScripts could fail for different reasons …”
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