Suchergebnisse - Obfuscated JavaScript~

Obfuscated Clone Search in JavaScript based on Reinforcement Subsequence Learning

Autoren: Leo Song Steven H. H. Ding Yuan Tian et al.

Quelle: ACM Transactions on Software Engineering and Methodology. 34:1-28

Detection and Analysis of Obfuscated and Minified JavaScript in the Croatian Web Space

Autoren: Toni Dujmović Bruno Skendrović Ivan Kovačević et al.

Quelle: 2023 46th MIPRO ICT and Electronics Convention (MIPRO). :1252-1257

Schlagwörter: JavaScript, cybersecurity, minification, automated detection, Croatian web space, obfuscation

Automatic Identification of Obfuscated JavaScript using Machine Learning

Autoren: Susana Maria de Sousa Lima

Schlagwörter: Engenharia electrotécnica, electrónica e informática, Electrical engineering, Electronic engineering, Information engineering

Dateibeschreibung: application/pdf

Verfügbarkeit: https://hdl.handle.net/10216/135504

Obfuscated JavaScript Code Detection using Machine Learning with AST-based Syntactic and Lexical Analysis

Autoren: Eren Kılıç Mehmet Tahir Sandıkkaya

Quelle: 2023 8th International Conference on Smart and Sustainable Technologies (SpliTech). :1-6

On improvements of robustness of obfuscated JavaScript code detection

Autoren: G. S. Ponomarenko P. G. Klyucharev

Quelle: Journal of Computer Virology and Hacking Techniques. 19:387-398

Schlagwörter: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Detection of Obfuscated Javascript Code Based on Abstract Syntax Trees Coloring

Autoren: G. S. Ponomarenko P. G. Klyucharev

Quelle: Mathematics and Mathematical Modeling. :1-24

Schlagwörter: 0102 computer and information sciences, 0101 mathematics, 01 natural sciences

Zugangs-URL: https://www.mathmelpub.ru/jour/article/download/218/167

Detecting Malicious Campaigns in Obfuscated JavaScript with Scalable Behavioral Analysis

Autoren: Oleksii Starov Yuchen Zhou Jun Wang

Quelle: 2019 IEEE Security and Privacy Workshops (SPW). :218-223

Schlagwörter: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Zugangs-URL: https://ieeexplore.ieee.org/ielx7/8834415/8844588/08844636.pdf

Detection of Obfuscated Malicious JavaScript Code

Autoren: Ammar Alazab Ansam Khraisat Moutaz Alazab et al.

Quelle: Future Internet, Vol 14, Iss 8, p 217 (2022)

Schlagwörter: malware detection, intrusion detection, obfuscated malicious, machine learning, malicious JavaScript, Information technology, T58.5-58.64

Dateibeschreibung: electronic resource

Relation: https://www.mdpi.com/1999-5903/14/8/217; https://doaj.org/toc/1999-5903

Zugangs-URL: https://doaj.org/article/e2fa7807e7e643e98d2b76506dbc7dd6

From Obfuscated to Obvious: A Comprehensive JavaScript Deobfuscation Tool for Security Analysis

Autoren: Zhou, Dongchao Ying, Lingyun Chai, Huajun et al.

Schlagwörter: Cryptography and Security, Software Engineering

Relation: http://arxiv.org/abs/2512.14070

Verfügbarkeit: http://arxiv.org/abs/2512.14070
https://doi.org/10.14722/ndss.2026.242198

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)

Detecting obfuscated JavaScripts using machine learning

Autoren: Aebersold, Simon Kryszczuk, Krzysztof Paganoni, Sergio et al.

Schlagwörter: Detection, Malicious JavaScript, Machine learning, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 006: Spezielle Computerverfahren, Obfuscated JavaScript

An Efficient Method for Detecting Obfuscated Suspicious JavaScript Based on Text Pattern Analysis

Autoren: Jiawei Su Katsunari Yoshioka Junji Shikata et al.

Quelle: Proceedings of the 2016 ACM International on Workshop on Traffic Measurements for Cybersecurity. :3-11

Schlagwörter: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Automated Threat Hunting for JavaScript-based Obfuscated Phishing Email Attachments

Autoren: Shewale, Saraunsh

Schlagwörter: Electronic computers. Computer science, Machine learning, Computer Security

Dateibeschreibung: application/pdf

Zugangs-URL: https://norma.ncirl.ie/7738/

MOJI: Character-level convolutional neural networks for Malicious Obfuscated JavaScript Inspection

Autoren: Minato Ishida Naoshi Kaneko Kazuhiko Sumi

Quelle: Applied Soft Computing. 137:110138

Schlagwörter: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 01 natural sciences, 0105 earth and related environmental sciences

JSObfusDetector: A binary PSO-based one-class classifier ensemble to detect obfuscated JavaScript code

Autoren: Mehran Jodavi Mahdi Abadi Elham Parhizkar

Quelle: 2015 The International Symposium on Artificial Intelligence and Signal Processing (AISP). :322-327

Schlagwörter: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Detecting Obfuscated JavaScript Malware Using Sequences of Internal Function Calls

Autoren: Alireza Gorji Mahdi Abadi

Quelle: Proceedings of the 2014 ACM Southeast Regional Conference. :1-6

Schlagwörter: 2. Zero hunger, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 16. Peace & justice

Detecting obfuscated JavaScripts using machine learning

Autoren: Aebersold, Simon Kryszczuk, Krzysztof Paganoni, Sergio et al.

Index Begriffe: Obfuscated JavaScript, Detection, Malicious JavaScript, Machine learning, 006: Spezielle Computerverfahren, Konferenz: Paper, Text

URL: https://doi.org/10.21256/zhaw-3848
ICIMP 2016 the Eleventh International Conference on Internet Monitoring and Protection : May 22-26, 2016, Valencia, Spain
ICIMP 2016 the Eleventh International Conference on Internet Monitoring and Protection, Valencia, Spain, 22-26 May 2016

Automatic Simplification of Obfuscated JavaScript Code: A Semantics-Based Approach

Autoren: Gen Lu Saumya Debray

Quelle: 2012 IEEE Sixth International Conference on Software Security and Reliability. :31-40

Schlagwörter: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Characterizing Obfuscated JavaScript Using Abstract Syntax Trees: Experimenting with Malicious Scripts

Autoren: Gregory Blanc Daisuke Miyamoto Mitsuaki Akiyama et al.

Quelle: 2012 26th International Conference on Advanced Information Networking and Applications Workshops. :344-351

Schlagwörter: 0202 electrical engineering, electronic engineering, information engineering, 0102 computer and information sciences, 02 engineering and technology, 01 natural sciences

JaSt: Fully Syntactic Detection of Malicious (Obfuscated) JavaScript

Autoren: Aurore Fass Robert P. Krawczyk Michael Backes et al.

Quelle: Lecture Notes in Computer Science ISBN: 9783319934105

Schlagwörter: 3. Good health