Results 81 to 90 of about 2,905 (223)
MalWhiteout: Reducing Label Errors in Android Malware Detection [PDF]
, 2023 Machine learning based Android malware detection has attracted a great deal of research work in recent years. A reliable malware dataset is critical to evaluate the effectiveness of malware detection approaches.
Wang, H, Wang, L, Luo, X, Sui, Y
core +1 more source
Robust AI‐SCORE Framework: Independent and Adversarial Validation for Malware Detection
Journal of Engineering, Volume 2026, Issue 1, 2026.Traditional malware detection methods such as signature‐based approaches and statistical analysis are becoming less effective in detecting the new breed of malware, which is holding high levels of complexity in terms of the number of code versions, compilation patterns, time to live (TTL), and jumping through evasion techniques.
Hafiz Talha Arif Zuberi +7 more
wiley +1 more source
Concept Drift Detection in Android Malware [PDF]
, 2023 Machine learning and deep learning algorithms have been successfully applied to the problems of malware detection, classification, and analysis. However, most of such studies have been limited to applying learning algorithms to a static snapshot of ...
Singh, Inderpreet
core +2 more sources
Alexandria Engineering JournalWith the fast growth of mobile phone usage, malicious threats against Android mobile devices are enhanced. The Android system utilizes a wide range of sensitive apps like banking apps; thus, it develops the aim of malware that uses the vulnerability of ...
Shoayee Dlaim Alotaibi +7 more
doaj +1 more source
Securing End‐To‐End Encrypted File Sharing Services With the Messaging Layer Security Protocol
Concurrency and Computation: Practice and Experience, Volume 37, Issue 27-28, 25 December 2025.ABSTRACT Secure file sharing is essential in today's digital environment, yet many systems remain vulnerable: if an attacker steals client keys, they can often decrypt both past and future content. To address this challenge, we propose a novel file‐sharing architecture that strengthens post‐compromise security while remaining practical.
Roland Helmich, Lars Braubach
wiley +1 more source
Android Malware Detection Using Backpropagation Neural Network [PDF]
, 2016 The rapid growing adoption of android operating system around the world affects the growth of malware that attacks this platform. One possible solution to overcome the threat of malware is building a comprehensive system to detect existing malware.
Herman Tolle +5 more
core +2 more sources
Advanced Intelligent Discovery, Volume 1, Issue 2, August 2025.This paper describes the basis for AInsectID Version 1, a GUI‐operable open‐source insect species identification, color processing, and image analysis software. This paper discusses our methods of algorithmic development, coupled to rigorous machine training used to enable high levels of validation accuracy.
Haleema Sadia, Parvez Alam
wiley +1 more source
Android Malware Detection Using Autoencoder
CoRR, 2019 9 Pages, 4 Figures, 3 ...
Abdelmonim Naway, Yuancheng Li
openaire +2 more sources
Contaminant removal for Android malware detection systems [PDF]
2017 IEEE International Conference on Big Data (Big Data), 2017 2017 IEEE International Conference on Big ...
Lichao Sun 0001 +5 more
openaire +2 more sources
Leveraging Ethical Narratives to Enhance LLM‐AutoML Generated Machine Learning Models
Expert Systems, Volume 42, Issue 7, July 2025.ABSTRACT The growing popularity of generative AI and large language models (LLMs) has sparked innovation alongside debate, particularly around issues of plagiarism and intellectual property law. However, a less‐discussed concern is the quality of code generated by these models, which often contains errors and encourages poor programming practices. This
Jordan Nelson +4 more
wiley +1 more source