A comprehensive survey on deep learning based malware detection techniques

M Gopinath, SC Sethuraman - Computer Science Review, 2023 - Elsevier
Recent theoretical and practical studies have revealed that malware is one of the most
harmful threats to the digital world. Malware mitigation techniques have evolved over the …

A survey on machine learning-based malware detection in executable files

J Singh, J Singh - Journal of Systems Architecture, 2021 - Elsevier
In last decade, a proliferation growth in the development of computer malware has been
done. Nowadays, cybercriminals (attacker) use malware as a weapon to carry out the …

Explainable artificial intelligence in cybersecurity: A survey

N Capuano, G Fenza, V Loia, C Stanzione - Ieee Access, 2022 - ieeexplore.ieee.org
Nowadays, Artificial Intelligence (AI) is widely applied in every area of human being's daily
life. Despite the AI benefits, its application suffers from the opacity of complex internal …

Human emotion recognition using deep belief network architecture

MM Hassan, MGR Alam, MZ Uddin, S Huda… - Information …, 2019 - Elsevier
Recently, deep learning methodologies have become popular to analyse physiological
signals in multiple modalities via hierarchical architectures for human emotion recognition …

Visualization and deep-learning-based malware variant detection using OpCode-level features

A Darem, J Abawajy, A Makkar, A Alhashmi… - Future Generation …, 2021 - Elsevier
Malicious software (malware) is a major threat to the systems and networks' security.
Although anti-malware products are used to protect systems and networks against malware …

A multimodal malware detection technique for Android IoT devices using various features

R Kumar, X Zhang, W Wang, RU Khan, J Kumar… - IEEE …, 2019 - ieeexplore.ieee.org
Internet of things (IoT) is revolutionizing this world with its evolving applications in various
aspects of life such as sensing, healthcare, remote monitoring, and so on. Android devices …

A system call refinement-based enhanced Minimum Redundancy Maximum Relevance method for ransomware early detection

YA Ahmed, B Koçer, S Huda, BAS Al-rimy… - Journal of Network and …, 2020 - Elsevier
Ransomware is a special type of malicious software that encrypts the user's assets and
makes it unavailable to the users until a ransom is paid to the ransomware author. Such …

A study on malicious software behaviour analysis and detection techniques: Taxonomy, current trends and challenges

P Maniriho, AN Mahmood, MJM Chowdhury - Future Generation Computer …, 2022 - Elsevier
There has been an increasing trend of malware release, which raises the alarm for security
professionals worldwide. It is often challenging to stay on top of different types of malware …

A weighted minimum redundancy maximum relevance technique for ransomware early detection in industrial IoT

YA Ahmed, S Huda, BAS Al-rimy, N Alharbi, F Saeed… - Sustainability, 2022 - mdpi.com
Ransomware attacks against Industrial Internet of Things (IIoT) have catastrophic
consequences not only to the targeted infrastructure, but also the services provided to the …

Ensemble dynamic behavior detection method for adversarial malware

C Jing, 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 …