Malware detection issues, challenges, and future directions: A survey

FA Aboaoja, A Zainal, FA Ghaleb, BAS Al-Rimy… - Applied Sciences, 2022 - mdpi.com
The evolution of recent malicious software with the rising use of digital services has
increased the probability of corrupting data, stealing information, or other cybercrimes by …

A survey of recent advances in deep learning models for detecting malware in desktop and mobile platforms

P Maniriho, AN Mahmood, MJM Chowdhury - ACM Computing Surveys, 2024 - dl.acm.org
Malware is one of the most common and severe cyber threats today. Malware infects
millions of devices and can perform several malicious activities including compromising …

Ensemble-based classification using neural networks and machine learning models for windows pe malware detection

R Damaševičius, A Venčkauskas, J Toldinas… - Electronics, 2021 - mdpi.com
The security of information is among the greatest challenges facing organizations and
institutions. Cybercrime has risen in frequency and magnitude in recent years, with new …

An Internet of Things assisted Unmanned Aerial Vehicle based artificial intelligence model for rice pest detection

SK Bhoi, KK Jena, SK Panda, HV Long… - Microprocessors and …, 2021 - Elsevier
Rice is a very essential food for the survival of human society. Most of the people focus on
production of rice for their financial gain as well as their survival in the society. Rice …

Automated machine learning for deep learning based malware detection

A Brown, M Gupta, M Abdelsalam - Computers & Security, 2024 - Elsevier
Deep learning (DL) has proven to be effective in detecting sophisticated malware that is
constantly evolving. Even though deep learning has alleviated the feature engineering …

A Survey of strategy-driven evasion methods for PE malware: transformation, concealment, and attack

J Geng, J Wang, Z Fang, Y Zhou, D Wu, W Ge - Computers & Security, 2024 - Elsevier
The continuous proliferation of malware poses a formidable threat to the cyberspace
landscape. Researchers have proffered a multitude of sophisticated defense mechanisms …

CTIMD: cyber threat intelligence enhanced malware detection using API call sequences with parameters

T Chen, H Zeng, M Lv, T Zhu - Computers & Security, 2024 - Elsevier
Dynamic malware analysis that monitors the sequences of API calls of the program in a
sandbox has been proven to be effective against code obfuscation and unknown malware …

Malbert: Using transformers for cybersecurity and malicious software detection

A Rahali, MA Akhloufi - arxiv preprint arxiv:2103.03806, 2021 - arxiv.org
In recent years we have witnessed an increase in cyber threats and malicious software
attacks on different platforms with important consequences to persons and businesses. It …

Static malware detection using stacked bilstm and gpt-2

D Demırcı, C Acarturk - IEEE Access, 2022 - ieeexplore.ieee.org
In recent years, cyber threats and malicious software attacks have been escalated on
various platforms. Therefore, it has become essential to develop automated machine …

Ensemble dynamic behavior detection method for adversarial malware

C **g, Y Wu, C Cui - Future Generation Computer Systems, 2022 - Elsevier
Behavior-based malware detection approaches combined with deep learning techniques
are effective against unknown malware and malware variants. However, such approaches …