Výsledky vyhledávání - "malicious JavaScripts"

Malicious JavaScript Detection by Features Extraction Autor Gerardo Canfora, Francesco Mercaldo, Corrado Aaron Visaggio

“… Existing techniques for detecting malicious JavaScripts could fail for different reasons…”
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A Discovery System of Malicious Javascript URLs hidden in Web Source Code Files Autor Park, Hweerang, Cho, Sang-Il, Park, Jungkyu, Cho, Youngho

“…One of serious security threats is a botnet-based attack. A botnet in general consists of numerous bots, which are computing devices with networking function,…”
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Detection of Obfuscated Malicious JavaScript Code Autor Alazab, Ammar, Khraisat, Ansam, Alazab, Moutaz, Singh, Sarabjot

“…Websites on the Internet are becoming increasingly vulnerable to malicious JavaScript code because of its strong impact and dramatic effect…”
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ZipAST: Enhancing malicious JavaScript detection with sequence compression Autor 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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Detecting malicious JavaScript code based on semantic analysis Autor Fang, Yong, Huang, Cheng, Su, Yu, Qiu, Yaoyao

“…Web development technology has undergone tremendous evolution, the creation of JavaScript has greatly enriched the interactive capabilities of the client…”
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Taylor–HHO algorithm: A hybrid optimization algorithm with deep long short‐term for malicious JavaScript detection Autor Alex, Scaria, Dhiliphan Rajkumar, T.

“… In addition, the attackers can easily induce malicious JavaScript into webpages for implanting attacks, like, phishing, spreading viruses, and Trojan horses…”
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JSContana: Malicious JavaScript detection using adaptable context analysis and key feature extraction Autor 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 Autor Fang, Yong, Huang, Chaoyi, Zeng, Minchuan, Zhao, Zhiying, Huang, Cheng

“…Web development technology has experienced significant progress. The creation of JavaScript has highly enriched the interactive ability of the client. However,…”
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Malicious JavaScript Detection Based on Bidirectional LSTM Model Autor 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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Research on Malicious JavaScript Detection Technology Based on LSTM Autor Fang, Yong, Huang, Cheng, Liu, Liang, Xue, Min

“…The attacker injects malicious JavaScript into web pages to achieve the purpose of implanting Trojan horses, spreading viruses, phishing, and obtaining secret information…”
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Raising the Bar Really High: An MTD Approach to Protect Data in Embedded Browsers Autor Mohsen, Fadi, Jafaarian, Haadi

“… For instance, an attacker in her WebView-Embedded app can inject malicious JavaScripts into the WebView to modify the web contents or to steal user's input values…”
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JSRevealer: A Robust Malicious JavaScript Detector against Obfuscation Autor Ren, Kunlun, Qiang, Weizhong, Wu, Yueming, Zhou, Yi, Zou, Deqing, Jin, Hai

“… As the main programming language for Web applications, many methods have been proposed for detecting malicious JavaScript, among which static analysis-based methods play an important role…”
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Detection of malicious javascript on an imbalanced dataset Autor 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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Spider bird swarm algorithm with deep belief network for malicious JavaScript detection Autor 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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Detecting Malicious JavaScript Using Structure-Based Analysis of Graph Representation Autor 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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Deobfuscation, unpacking, and decoding of obfuscated malicious JavaScript for machine learning models detection performance improvement Autor Ndichu, Samuel, Kim, Sangwook, Ozawa, Seiichi

“…Obfuscation is rampant in both benign and malicious JavaScript (JS) codes. It generates an obscure and undetectable code that hinders comprehension and analysis…”
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TransAST: A Machine Translation-Based Approach for Obfuscated Malicious JavaScript Detection Autor Qin, Yan, Wang, Weiping, Chen, Zixian, Song, Hong, Zhang, Shigeng

“…s. Although researchers are constantly proposing methods to detect malicious JavaScript, the emergence of obfuscation technology makes it difficult for previous approaches to detect disguised malicious…”
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ScriptNet: Neural Static Analysis for Malicious JavaScript Detection Autor 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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PyRHOH: A meta-learning analysis framework for determining the impact of compilation on malicious JavaScript identification Autor Fulkerson, Eli, Yocam, Eric, Vaidyan, Varghese, Kamepalli, Mahesh, Wang, Yong, Comert, Gurcan

“…Automated identification of malicious JavaScript is a core problem within modern malware analysis…”
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Malicious JavaScript Code Detection Based on Hybrid Analysis Autor 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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