@inproceedings{251b547419634e04bfc5114561dedb52,
title = "A Systematic Literature Review on the Mobile Malware Detection Methods",
abstract = "With the advent of the 5G network, the number of mobile users has drastically increased. Consequently, the users are much more susceptible to cyber-attacks such as mobile malware. In order to combat mobile malware, recent studies have employed machine learning techniques. This paper revisits existing research on machine learning-based mobile malware detection in cybersecurity. Our study focuses on subjects such as mobile system destruction and information leaks. We explore the mobile malware detection techniques utilized in recent studies based on the attack intentions such as (i) Server, (ii) Network, (iii) Client Software, (iv) Client Hardware, and (v) User. We hope our study can provide future research directions and a framework for a thorough evaluation. Furthermore, we review and summarize security challenges related to cybersecurity that can lead to improved and more practical research.",
keywords = "Dataset properties, Machine learning, Mobile detection, Mobile malware",
author = "Kim, {Yu kyung} and Lee, {Jemin Justin} and Go, {Myong Hyun} and Kang, {Hae Young} and Kyungho Lee",
note = "Funding Information: Supported by Defense Acquisition Program Administration and Agency for Defense Development under the contract (UD190016ED), and a grant of the Korean Heath Technology R&D Project, Ministry of Health and Welfare, Republic of Korea (HI19C0866). Publisher Copyright: {\textcopyright} 2022, Springer Nature Singapore Pte Ltd.; 5th International Symposium on Mobile Internet Security, MobiSec 2021 ; Conference date: 07-10-2021 Through 09-10-2021",
year = "2022",
doi = "10.1007/978-981-16-9576-6_19",
language = "English",
isbn = "9789811695759",
series = "Communications in Computer and Information Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "263--288",
editor = "Ilsun You and Hwankuk Kim and Taek-Young Youn and Francesco Palmieri and Igor Kotenko",
booktitle = "Mobile Internet Security - 5th International Symposium, MobiSec 2021, Revised Selected Papers",
address = "Germany",
}