A survey of stealth malware attacks, mitigation measures, and steps toward autonomous open world solutions

EM Rudd, A Rozsa, M Günther… - … Surveys & Tutorials, 2016 - ieeexplore.ieee.org
As our professional, social, and financial existences become increasingly digitized and as
our government, healthcare, and military infrastructures rely more on computer technologies …

Malware detection employed by visualization and deep neural network

A Pinhero, ML Anupama, P Vinod, CA Visaggio… - Computers & …, 2021 - Elsevier
With the fast growth of malware's volume circulating in the wild, to obtain a timely and correct
classification is increasingly difficult. Traditional approaches to automatic classification suffer …

Dynamic android malware category classification using semi-supervised deep learning

S Mahdavifar, AFA Kadir, R Fatemi… - 2020 IEEE Intl Conf …, 2020 - ieeexplore.ieee.org
Due to the significant threat of Android mobile malware, its detection has become
increasingly important. Despite the academic and industrial attempts, devising a robust and …

Toward developing a systematic approach to generate benchmark android malware datasets and classification

AH Lashkari, AFA Kadir, L Taheri… - … conference on security …, 2018 - ieeexplore.ieee.org
Malware detection is one of the most important factors in the security of smartphones.
Academic researchers have extensively studied Android malware detection problems …

Extensible android malware detection and family classification using network-flows and API-calls

L Taheri, AFA Kadir, AH Lashkari - … Carnahan conference on …, 2019 - ieeexplore.ieee.org
Android OS-based mobile devices have attracted numerous end-users since they are
convenient to work with and offer a variety of features. As a result, Android has become one …

A method for automatic android malware detection based on static analysis and deep learning

M İbrahim, B Issa, MB Jasser - IEEE Access, 2022 - ieeexplore.ieee.org
The computers nowadays are being replaced by the smartphones for the most of the internet
users around the world, and Android is getting the most of the smartphone systems' market …

On the use of artificial malicious patterns for android malware detection

M Jerbi, ZC Dagdia, S Bechikh, LB Said - Computers & Security, 2020 - Elsevier
Malware programs currently represent the most serious threat to computer information
systems. Despite the performed efforts of researchers in this field, detection tools still have …

Android malware detection and classification based on network traffic using deep learning

M Gohari, S Hashemi, L Abdi - 2021 7th International …, 2021 - ieeexplore.ieee.org
Users of smartphones in the world has grown significantly, and attacks against these
devices have increased. Many protection techniques for android malware detection have …

Cross-method-based analysis and classification of malicious behavior by api calls extraction

B Ndibanje, KH Kim, YJ Kang, HH Kim, TY Kim… - Applied Sciences, 2019 - mdpi.com
Data-driven public security networking and computer systems are always under threat from
malicious codes known as malware; therefore, a large amount of research and development …

Identifying malicious software using deep residual long-short term memory

A Alotaibi - IEEE Access, 2019 - ieeexplore.ieee.org
The use of smartphone applications based on the Android OS platform is rapidly growing
among smartphone users. However, malicious apps for Android are being developed to …