Android malware classification based on random vector functional link and artificial Jellyfish Search optimizer.

ABSTRACT: Smartphone usage is nearly ubiquitous worldwide, and Android provides the leading open-source operating system, retaining the most significant market share and active user population of all open-source operating systems. Hence, malicious actors target the Android operating system to capitalize on this consumer reliance and vulnerabilities present in the system. Hackers often use confidential user data to exploit users for advertising, extortion, and theft. Notably, most Android malware detection tools depend on conventional machine-learning algorithms; hence, they lose the benefits of metaheuristic optimization. Here, we introduce a novel detection system based on optimizing the random vector functional link (RVFL) using the artificial Jellyfish Search (JS) optimizer following dimensional

SUBMITTER: Elkabbash ET 

PROVIDER: S-EPMC8604294 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature