Year: 2025
Type: article
Abstract: The proliferation of messaging applications has introduced new security challenges, with messenger application cloning emerging as a significant threat to user privacy and data security.This paper presents a comprehensive analysis of messenger application cloning techniques, their potential impact on user security, and proposed detection methodologies.Through extensive research and empirical analysis, we examine how malicious actors exploit vulnerabilities in popular messaging platforms to create unauthorized clones, potentially compromising sensitive user data and communications.Our investigation reveals that current detection methods, while partially effective, have limitations in identifying sophisticated cloning techniques that employ advanced obfuscation methods.To address these challenges, we propose a novel framework that combines static analysis, dynamic behavioural detection, and machine learning algorithms to identify and prevent messenger application cloning.Our experimental results demonstrate that the proposed framework achieves a 94% detection rate for cloned applications while maintaining a false positive rate below 2%.Furthermore, we discuss the implementation of preventive measures and security protocols that can be adopted by messaging platform developers to enhance resistance against cloning attempts.This research contributes to the growing body of knowledge in mobile application security and provides practical solutions for protecting users against the emerging threat of messenger application cloning.
DOI: 10.31871/wjrr.20.2.3
Authors: B. KALAISELVI, R. NIVETHA, J. PAVITHRA, V. PRADITHA, S. VISHNUPRIYA
Language: English
Subfield: Signal Processing
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4409347488