Results 61 to 70 of about 20,046 (244)

Static analysis framework for permission-based dataset generation and android malware detection using machine learning

EURASIP Journal on Information Security
Since Android is the popular mobile operating system worldwide, malicious attackers seek out Android smartphones as targets. The Android malware can be identified through a number of established detection techniques.
Amarjyoti Pathak, Th. Shanta Kumar, Utpal Barman   +2 more
doaj   +1 more source

TTGNet-AMD: Android malware detection based on multi-modal feature fusion [PDF]

PeerJ Computer Science
The application of static features for Android malware detection has been extensively studied and developed. Existing methods exhibit limitations in both the completeness and discriminability of feature representation, which affects the enhancement of ...
Jiayin Feng, Meiyu Wang, JinLing Song, Chenfeng Yang, Lingzu Zhang, Yang Shen   +5 more
doaj   +2 more sources

Improved chimp optimization algorithm (ICOA) feature selection and deep neural network framework for internet of things (IOT) based android malware detection

Measurement: Sensors, 2023
Internet of Things (IoT) is extensively implemented using Android applications thus detecting malicious Android apps is necessary. Malicious has been multiplying fast as a result of the growing usage of smartphones.
Tirumala Vasu G, Samreen Fiza, ATA. Kishore Kumar, V. Sowmya Devi, Ch Niranjan Kumar, Afreen Kubra   +5 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

AInsectID Version 1.1: An Insect Species Identification Software Based on the Transfer Learning of Deep Convolutional Neural Networks

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

AndroMalPack: enhancing the ML-based malware classification by detection and removal of repacked apps for Android systems

Scientific Reports, 2022
Due to the widespread usage of Android smartphones in the present era, Android malware has become a grave security concern. The research community relies on publicly available datasets to keep pace with evolving malware.
Husnain Rafiq, Nauman Aslam, Muhammad Aleem, Biju Issac, Rizwan Hamid Randhawa   +4 more
doaj   +1 more source

Android Malware Detection Using Deep Learning

, 2022
This chapter investigates the potential of deep learning architectures for Android malware detection, specifically convolutional neural networks (CNNs) using natural language processing (NLP) concepts. The proposed solution is based on static analysis of raw opcode sequences from disassembled programs and other complementary features such as API calls ...
Millar, Stuart, McLaughlin, Niall, Martinez-del-Rincon, Jesus, Miller, Paul   +3 more
openaire   +3 more sources

Security in Metaverse Markets: Challenges and Solutions—A Comprehensive Review

Expert Systems, Volume 42, Issue 8, August 2025.
ABSTRACT This review paper provides a systematic overview of the metaverse markets security problems and solutions. The metaverse is an emerging digital space, bridging virtual, augmented and mixed reality environments. As the metaverse evolves, issues related to customer security have emerged, which include breaches of privacy, thefts of identity and ...
Mohammad Z. Aloudat, Mahmoud Barhamgi, Elias Yaacoub, Dani Aoun   +3 more
wiley   +1 more source

A Survey and Evaluation of Android-Based Malware Evasion Techniques and Detection Frameworks

Information, 2023
Android platform security is an active area of research where malware detection techniques continuously evolve to identify novel malware and improve the timely and accurate detection of existing malware.
Parvez Faruki, Rati Bhan, Vinesh Jain, Sajal Bhatia, Nour El Madhoun, Rajendra Pamula   +5 more
doaj   +1 more source

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, Michalis Pavlidis, Andrew Fish, Nikolaos Polatidis, Yannis Manolopoulos   +4 more
wiley   +1 more source