Suchergebnisse - JavaScript malicious code

A Combined Model for JavaScript Malicious Code Detection Based on Deep Q-Networks

Autoren: Wenming Wang Hongru Song Jiaolong Zheng

Quelle: Proceedings of the 2025 5th International Conference on Automation Control, Algorithm and Intelligent Bionics. :344-349

Systems and methods for causing nonpredictable environment states for exploit prevention and malicious code neutralization for javascript-enabled applications

Systems and methods for exploit prevention and malicious code neutralization using non-predictable results for JavaScript-enabled applications

SYSTEMS AND METHODS FOR CAUSING NONPREDICTABLE ENVIRONMENT STATES FOR EXPLOIT PREVENTION AND MALICIOUS CODE NEUTRALIZATION FOR JAVASCRIPT-ENABLED APPLICATIONS

Systems and methods for causing nonpredictable environment states for exploit prevention and malicious code neutralization for JavaScript-enabled applications

JACLNet:Application of adaptive code length network in JavaScript malicious code detection.

Autoren: Zhining Zhang Liang Wan Kun Chu et al.

Quelle: PLoS ONE, Vol 17, Iss 12, p e0277891 (2022)

Schlagwörter: Medicine, Science

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/1932-6203

Zugangs-URL: https://doaj.org/article/eb6a9c9af180452ca1ce0ad7d3428689

Detection of Obfuscated Malicious JavaScript Code.

Autoren: Alazab, Ammar Khraisat, Ansam Alazab, Moutaz et al.

Quelle: Future Internet. Aug2022, Vol. 14 Issue 8, p217-N.PAG. 15p.

Schlagwörter: *JavaScript programming language, *Machine learning, *Internet users, *Cyberterrorism, *Malware, *Websites, Intrusion detection systems (Computer security)

SYSTEMS AND METHODS FOR CAUSING NONPREDICTABLE ENVIRONMENT STATES FOR EXPLOIT PREVENTION AND MALICIOUS CODE NEUTRALIZATION FOR JAVASCRIPT-ENABLED APPLICATIONS

SYSTEMS AND METHODS FOR EXPLOIT PREVENTION AND MALICIOUS CODE NEUTRALIZATION USING NON-PREDICTABLE RESULTS FOR JAVASCRIPT-ENABLED APPLICATIONS

Systems and methods for causing nonpredictable environment states for exploit prevention and malicious code neutralization for javascript-enabled applications

Systems and methods for exploit prevention and malicious code neutralization using non-predictable results for JavaScript-enabled applications

SYSTEMS AND METHODS FOR CAUSING NONPREDICTABLE ENVIRONMENT STATES FOR EXPLOIT PREVENTION AND MALICIOUS CODE NEUTRALIZATION FOR JAVASCRIPT-ENABLED APPLICATIONS

SYSTEMS AND METHODS FOR EXPLOIT PREVENTION AND MALICIOUS CODE NEUTRALIZATION USING NON-PREDICTABLE RESULTS FOR JAVASCRIPT-ENABLED APPLICATIONS

Research on Malicious JavaScript Detection Technology Based on LSTM

Autoren: Yong Fang Cheng Huang Liang Liu et al.

Quelle: IEEE Access, Vol 6, Pp 59118-59125 (2018)

Schlagwörter: JavaScript, malicious code detection, bytecode, word vector, LSTM, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Dateibeschreibung: electronic resource

Relation: https://ieeexplore.ieee.org/document/8482113/; https://doaj.org/toc/2169-3536

Zugangs-URL: https://doaj.org/article/10eaad4b416443e996b2dfbad65517e4

Behavior Analysis Usage with Behavior Tures Adoption for Malicious Code Detection on JAVASCRIPT Scenarios Example

Autoren: Y. M. Tumanov S.V. Gavrilyuk

Quelle: Безопасность информационных технологий, Vol 17, Iss 1, Pp 115-117 (2010)

Schlagwörter: malicious code detection, behavior analysis, behavior signature, Information technology, T58.5-58.64, Information theory, Q350-390

Dateibeschreibung: electronic resource

Relation: https://bit.mephi.ru/index.php/bit/article/view/791; https://doaj.org/toc/2074-7128; https://doaj.org/toc/2074-7136

Zugangs-URL: https://doaj.org/article/1ee7b69964a2440c926708454e78aada

JACLNet:Application of adaptive code length network in JavaScript malicious code detection.

Autoren: Zhang, Zhining Wan, Liang Chu, Kun et al.

Quelle: PLoS ONE; 12/14/2022, Vol. 17 Issue 12, p1-27, 27p

Schlagwörter: DEEP learning, JAVASCRIPT programming language, LINEAR network coding, FEATURE extraction, DATA mining, INFORMATION modeling, SYNTAX (Grammar)

An improved bytecode similarity measurement for malicious JavaScript code detection

一個改良位元組碼相似度計算之JavaScript惡意程式偵測方法

Autoren: Jun-Xu Yang 楊鈞旭

Thesis Advisors: Jun-Xu Yang 楊鈞旭

Dateibeschreibung: 31

Verfügbarkeit: http://ndltd.ncl.edu.tw/handle/dyhtkn

Analysis and Identification of Malicious JavaScript Code.

Autoren: Fraiwan, Mohammad Al-Salman, Rami Khasawneh, Natheer et al.

Quelle: Information Security Journal: A Global Perspective; 2012, Vol. 21 Issue 1, p1-11, 11p

Schlagwörter: JAVASCRIPT programming language, MALWARE, SCRIPTING languages (Computer science), WEBSITES, PHISHING

A Systematic Literature Review and Quality Analysis of Javascript Malware Detection

Autoren: Md. Fahimuzzman Sohan Anas Basalamah

Quelle: IEEE Access, Vol 8, Pp 190539-190552 (2020)

Schlagwörter: Cybersecurity, systematic literature review, malicious code detection, javascript attacks, javascript malware detection, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Dateibeschreibung: electronic resource

Relation: https://ieeexplore.ieee.org/document/9226527/; https://doaj.org/toc/2169-3536

Zugangs-URL: https://doaj.org/article/166a15a34eb547178523936e1969c86f

This paper proposes a JavaScript malicious code detection method framework.

Autoren: Zhining Zhang (10583870) Liang Wan (119472) Kun Chu (11727827) et al.

Schlagwörter: Cancer, Science Policy, Biological Sciences not elsewhere classified, Mathematical Sciences not elsewhere classified, Information Systems not elsewhere classified, conduct comparative experiments, 87 %, higher, 32 %, short javascript code, original dataset db_or, existing methods based, enhanced dataset db_re, div >< p, convolutional block rdcnet, distance association features, association features, 72 %, variable distance, subsequent models, score <, model presented, method ’, jacnet improved, feature extraction, f <, deep learning, datasets used, capture short, 79 %

Relation: https://figshare.com/articles/figure/This_paper_proposes_a_JavaScript_malicious_code_detection_method_framework_/21727212

Verfügbarkeit: https://doi.org/10.1371/journal.pone.0277891.g001