Search Results - "Obfuscation JavaScript"

Suspicious Malicious Web Site Detection with Strength Analysis of a

Authors: Javascript Obfuscation Byung-ik Kim Chae-tae Im et al.

Contributors: Javascript Obfuscation Byung-ik Kim Chae-tae Im et al.

Source: http://www.sersc.org/journals/IJAST/vol26/2.pdf.

Subject Terms: Malicious Web Sites, Obfuscation JavaScript, Entropy, Frequency, Density

File Description: application/pdf

Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.359.7432; http://www.sersc.org/journals/IJAST/vol26/2.pdf

Availability: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.359.7432
http://www.sersc.org/journals/IJAST/vol26/2.pdf

Real-Time Phishing Detection for Brand Protection Using Temporal Convolutional Network-Driven URL Sequence Modeling.

Authors: Alorvor, Marie-Laure E. Dadkhah, Sajjad

Source: Electronics (2079-9292); Sep2025, Vol. 14 Issue 18, p3746, 39p

Subject Terms: PHISHING, CONVOLUTIONAL neural networks, INTERNET security, MACHINE learning, TRADEMARKS

Survey of Transformer-Based Malicious Software Detection Systems.

Authors: Alshomrani, Mohammed Albeshri, Aiiad Alturki, Badraddin et al.

Source: Electronics (2079-9292); Dec2024, Vol. 13 Issue 23, p4677, 34p

Subject Terms: TRANSFORMER models, MACHINE learning, MALWARE, DEEP learning, CYBERTERRORISM, RANSOMWARE

A comprehensive survey of phishing: mediums, intended targets, attack and defence techniques and a novel taxonomy.

Authors: Goenka, Richa Chawla, Meenu Tiwari, Namita

Source: International Journal of Information Security; Apr2024, Vol. 23 Issue 2, p819-848, 30p

Subject Terms: PHISHING, ONLINE databases, PHISHING prevention, COVID-19 pandemic, TAXONOMY, COVID-19, SCIENCE publishing

On improvements of robustness of obfuscated JavaScript code detection.

Authors: Ponomarenko, G. S. Klyucharev, P. G.

Source: Journal of Computer Virology & Hacking Techniques; Sep2023, Vol. 19 Issue 3, p387-398, 12p

A Combined Static and Dynamic Analysis Approach to Detect Malicious Browser Extensions.

Authors: Wang, Yao Cai, Wandong Lyu, Pin et al.

Source: Security & Communication Networks; 5/2/2018, p1-16, 16p

Subject Terms: WEB browsers, JAVASCRIPT programming language, EXTENSIONS, FEATURE selection, SOURCE code

Deep belief network based detection and categorization of malicious URLs.

Authors: Selvaganapathy, ShymalaGowri Nivaashini, Mathappan Natarajan, HemaPriya

Source: Information Security Journal: A Global Perspective; 2018, Vol. 27 Issue 3, p145-161, 17p

Subject Terms: UNIFORM Resource Locators, MALWARE, CYBERTERRORISM, ARTIFICIAL neural networks, DEEP learning, BOLTZMANN machine, K-nearest neighbor classification

Detecting Obfuscated Suspicious JavaScript Based on Information-Theoretic Measures and Novelty Detection.

Authors: Su, Jiawei Yoshioka, Katsunari Shikata, Junji et al.

Source: Information Security & Cryptology - ICISC 2015; 2016, p278-293, 16p

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

Authors: Jodavi, Mehran Abadi, Mahdi Parhizkar, Elham

Source: 2015 The International Symposium on Artificial Intelligence & Signal Processing (AISP); 2015, p322-327, 6p

Comparison of Multi-objective Optimization Algorithms for the JShadObf JavaScript Obfuscator.

Authors: Bertholon, Benoit Varrette, Sebastien Bouvry, Pascal

Source: 2014 IEEE International Parallel & Distributed Processing Symposium Workshops; 2014, p489-496, 8p

RedJsod: A Readable JavaScript Obfuscation Detector Using Semantic-based Analysis.

Authors: AL-Taharwa, Ismail Adel Lee, Hahn-Ming Jeng, Albert B. et al.

Source: 2012 IEEE 11th International Conference on Trust, Security & Privacy in Computing & Communications; 1/ 1/2012, p1370-1375, 6p

Using HTML5 to prevent detection of drive-by-download web malware.

Authors: De Santis, Alfredo De Maio, Giancarlo Petrillo, Umberto Ferraro

Source: Security & Communication Networks; May2015, Vol. 8 Issue 7, p1237-1255, 19p

Subject Terms: HTML (Document markup language), DOCUMENT markup languages, HYPERTEXT systems, WEB development, MALWARE

Single Page Web Applications Security.

Authors: BEDA, Bogdan

Source: Journal of Mobile, Embedded & Distributed Systems; 2015, Vol. 7 Issue 2, p54-59, 6p

Subject Terms: WEB-based user interfaces, SECURITY management, INTERNET access, COMPUTER hackers, COMPUTER security

JShadObf: A JavaScript Obfuscator Based on Multi-Objective Optimization Algorithms

Authors: Bertholon, Benoit Varrette, Sébastien Bouvry, Pascal

Index Terms: Obfuscation; JavaScript Compilation; MOEA, info:eu-repo/semantics/conferenceObject

URL: http://orbilu.uni.lu/handle/10993/10154
http://orbilu.uni.lu/bitstream/10993/10154/1/jshadobf.pdf

Learn Penetration Testing with Python 3.x - 2nd Edition

Authors: Yehia Elghaly

Resource Type: eBook.

Subjects: Python (Computer program language), Video games--Programming, Computer programming

Categories: COMPUTERS / Languages / Python, COMPUTERS / Operating Systems / Windows Server, COMPUTERS / Programming / General

Pen Testing From Contract to Report

Authors: Alfred Basta Nadine Basta Waqar Anwar

Resource Type: eBook.

Categories: COMPUTERS / Security / General

R Bioinformatics Cookbook : Utilize R Packages for Bioinformatics, Genomics, Data Science, and Machine Learning

Authors: MacLean

Resource Type: eBook.

Subjects: Computational biology, R (Computer program language), Bioinformatics

Categories: COMPUTERS / Data Science / Data Visualization, COMPUTERS / Data Science / General, TECHNOLOGY & ENGINEERING / Biomedical

Data Mining and Big Data

Authors: Ying Tan Yuhui Shi Albert Zomaya et al.

Resource Type: eBook.

Subjects: Application software, Computer networks, Artificial intelligence, Data protection

Categories: COMPUTERS / Business & Productivity Software / General, COMPUTERS / Artificial Intelligence / General, COMPUTERS / Networking / General, COMPUTERS / Security / General

Learn Penetration Testing with Python 3.x

Authors: Yehia Elghaly

Resource Type: eBook.

Categories: COMPUTERS / Languages / Python, COMPUTERS / Software Development & Engineering / Quality Assurance & Testing

Data Science in Cybersecurity and Cyberthreat Intelligence

Authors: Leslie F. Sikos Kim-Kwang Raymond Choo

Resource Type: eBook.

Subjects: Computer security

Categories: COMPUTERS / Data Science / General, COMPUTERS / Artificial Intelligence / General, COMPUTERS / Security / General, SOCIAL SCIENCE / Criminology, TECHNOLOGY & ENGINEERING / Engineering (General)