Search Results - python obfuscator*

Secure Python Code Manager: A Tool for Secure Code Sharing and Protection in Python Programming

Authors: Izosimov, Pavel

Subject Terms: Alpha Beta Network, code protection, cloud platform, secure code sharing, code security, python obfuscator, secure file transfer, code obfuscation, intellectual property protection, software licensing, secure distribution, python development, python code encryption, license management, python security, source code protection

Evading Antivirus Software Detection Using Python and PowerShell Obfuscation Framework

Authors: Anggy Pradiftha Haris Al Qodri Maarif Teddy Mantoro et al.

Source: MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer. 22:519-528

Розробка та застосування обфускатора для кіберзахисту об’єктів критичної інфраструктур. (Ukrainian)

Alternate Title: DEVELOPMENT AND APPLICATION OF AN OBFUSCATOR FOR CYBERSECURITY OF CRITICAL INFRASTRUCTURE OBJECTS. (English)

Authors: Заїка, Н. В. Верховець, О. С. Комаров, М. Ю. et al.

Source: Èlektronnoe Modelirovanie; 2025, Vol. 47 Issue 4, p49-56, 8p

Subject Terms: REVERSE engineering, MALWARE, SOFTWARE development tools, INTERNET security, COMPUTER performance, INFORMATION technology

Exploring Android Obfuscators and Deobfuscators: An Empirical Investigation.

Authors: Ebad, Shouki A. Darem, Abdulbasit A.

Source: Electronics (2079-9292); Jun2024, Vol. 13 Issue 12, p2272, 15p

Subject Terms: PROGRAMMING languages, COMPUTER science, RESEARCH personnel, ACADEMIC programs, SMARTPHONES, SALINE injections

ShadObf: A C-Source Obfuscator Based on Multi-objective Optimisation Algorithms

Authors: BERTHOLON, Benoit VARRETTE, Sebastien Martinez, Sebastien

Source: urn:isbn:978-0-7695-4979-8 ; Proceedings of the 2013 IEEE 27th International Symposium on Parallel and Distributed Processing Workshops and PhD Forum, 435--444 (2013); 27th International Symposium on Parallel and Distributed Processing Workshops, 05-2013

Subject Terms: Evolutionary Algorithm, Multi Objective Evolutionary Algorithm, Software Obfuscation, Source-to-source Compilation, NSGA-II, PIPS, Python, Engineering, computing & technology, Computer science, Ingénierie, informatique & technologie, Sciences informatiques

Relation: http://dx.doi.org/10.1109/IPDPSW.2013.234; https://orbilu.uni.lu/handle/10993/10156; info:hdl:10993/10156

Availability: https://orbilu.uni.lu/handle/10993/10156
https://doi.org/10.1109/IPDPSW.2013.234

Classification of Obfuscation Techniques in LLVM IR: Machine Learning on Vector Representations.

Authors: Raubitzek, Sebastian Felbauer, Patrick Mallinger, Kevin et al.

Source: Machine Learning & Knowledge Extraction; Dec2025, Vol. 7 Issue 4, p125, 29p

Subject Terms: MACHINE learning, STATISTICAL accuracy

Large-scale and Robust Code Authorship Identification with Deep Feature Learning.

Authors: ABUHAMAD, MOHAMMED ABUHMED, TAMER MOHAISEN, DAVID et al.

Source: ACM Transactions on Privacy & Security; Sep2021, Vol. 24 Issue 4, p1-35, 35p

Subject Terms: FEATURE extraction, SOURCE code, PROGRAMMING languages, DEEP learning, RECURRENT neural networks

Code Obfuscation: A Comprehensive Approach to Detection, Classification, and Ethical Challenges.

Authors: Raitsis, Tomer Elgazari, Yossi Toibin, Guy E. et al.

Source: Algorithms; Feb2025, Vol. 18 Issue 2, p54, 20p

Subject Terms: REVERSE engineering, COMPUTER software development, INTELLECTUAL property, RANDOM forest algorithms, TRADE secrets

Enhancing Security: Devanagari Handwritten CAPTCHA Generation using Digital Handwritten Devanagari Character Dataset.

Authors: Pate, Sanjay E. Ramteke, Rakesh J.

Source: Grenze International Journal of Engineering & Technology (GIJET); Jan2025, Vol. 11 Issue Part1, p645-653, 9p

Subject Terms: SPECKLE interference, LINGUISTIC context, TURING test, LINGUISTIC landscapes, GRAYSCALE model

Python for Business Analytics

Authors: Mahadi Hasan Miraz Narishah Mohamed Salleh Hwang Ha Jin

Resource Type: eBook.

Categories: COMPUTERS / Business & Productivity Software / Business Intelligence

An empirical study on the effectiveness of large language models for binary code understanding.

Authors: Shang, Xiuwei Fu, Zhenkan Cheng, Shaoyin et al.

Source: Empirical Software Engineering; Feb2026, Vol. 31 Issue 1, p1-38, 38p

Malware Classification Using Cyclic Reconstruction Contractive Loss based Bidirectional Feed Forward Neural Network.

Authors: Manjappa Narahari, Nagaraj Shet Ramegowda, Jagadeesha

Source: International Journal of Intelligent Engineering & Systems; 2026, Vol. 19 Issue 1, p114-127, 14p

Subject Terms: MALWARE, FEEDFORWARD neural networks, FEATURE extraction, PATTERN perception, LOSS functions (Statistics), STATISTICAL reliability, ARTIFICIAL neural networks, MACHINE learning

Programming Python : Powerful Object-Oriented Programming

Authors: Mark Lutz

Resource Type: eBook.

Subjects: Python (Computer program language)

Categories: COMPUTERS / Languages / Python, COMPUTERS / Programming / General, COMPUTERS / Programming / Object Oriented, COMPUTERS / Programming / Open Source

Obfuscation Combiners.

Authors: Fischlin, Marc Herzberg, Amir Bin-Noon, Hod et al.

Source: Advances in Cryptology - CRYPTO 2016: 36th Annual International Cryptology Conference, Santa Barbara, CA, USA, August 14-18, 2016, Proceedings, Part II; 2016, p521-550, 30p

A State-of-the-Art Survey of Adversarial Reinforcement Learning for IoT Intrusion Detection.

Authors: Al-Haija, Qasem Abu Tamimi, Shahad Al

Source: Computers, Materials & Continua; 2026, Vol. 87 Issue 1, p1-69, 69p

Subject Terms: INTRUSION detection systems (Computer security), REINFORCEMENT learning, INTERNET security, COMPUTER network security, ADVERSARIAL machine learning

Enhancing security in IIoT: RFID authentication protocol for edge computing and blockchain-enabled supply chain.

Authors: Kumar, Vikash Das, Santosh Kumar

Source: Cyber Security & Applications; Dec2025, Vol. 3, p1-17, 17p

Subject Terms: RADIO frequency identification systems, EDGE computing, CRYPTOGRAPHY, SECURITY management, ENCRYPTION protocols, CYBER physical systems, BLOCKCHAINS

Semantic-aware framework for zero-shot malware classification via attention-based relation network.

Authors: Khan, Faiza Babar Tayyab, Umm-e-Hani Durad, Muhammad Hanif et al.

Source: PeerJ Computer Science; Dec2025, p1-24, 24p

Subject Terms: MALWARE, CLASSIFICATION, MACHINE learning, ARTIFICIAL neural networks, FALSE positive error

Toward a Robust Detection of PowerShell Malware against Code Mixing and Obfuscation by Using Sentence Transformer and Similarity Learning.

Authors: Fu, Zhiwei Song, Leo Ding, Steven et al.

Source: ACM Transactions on Privacy & Security; Nov2025, Vol. 28 Issue 4, p1-23, 23p

Subject Terms: MALWARE, MACHINE learning, PATTERN perception, MALWARE prevention, SCRIPTING languages (Computer science), ARTIFICIAL neural networks

Robust Hashing for Improved CNN Performance in Image-Based Malware Detection.

Authors: Kulkarni, Sanket Shekhar Di Troia, Fabio

Source: Electronics (2079-9292); Oct2025, Vol. 14 Issue 19, p3915, 20p

Subject Terms: CONVOLUTIONAL neural networks, MALWARE, CLASSIFICATION, ARTIFICIAL neural networks

Decoding the Solution for Man-at-the-End Attacks and Reverse Engineering on IoMT Devices: An Experimental Review of Techniques and Defences.

Authors: T, Agila Harshini Sriraman, Harini

Source: Journal of Multidisciplinary Healthcare; Oct2025, Vol. 18, p6479-6501, 23p

Subject Terms: INTERNET of medical things, REVERSE engineering, CYBERTERRORISM, SECURITY management, ANOMALY detection (Computer security), FIELD programmable gate arrays, MEDICAL equipment