Malware detection and prevention using artificial intelligence techniques

MJH Faruk, H Shahriar, M Valero… - … conference on big …, 2021 - ieeexplore.ieee.org
With the rapid technological advancement, security has become a major issue due to the
increase in malware activity that poses a serious threat to the security and safety of both …

Securing tomorrow: a comprehensive survey on the synergy of Artificial Intelligence and information security

E Hashmi, MM Yamin, SY Yayilgan - AI and Ethics, 2024 - Springer
This survey paper explores the transformative role of Artificial Intelligence (AI) in information
security. Traditional methods, especially rule-based approaches, faced significant …

Machine learning adoption in blockchain-based smart applications: The challenges, and a way forward

S Tanwar, Q Bhatia, P Patel, A Kumari, PK Singh… - IEEE …, 2019 - ieeexplore.ieee.org
In recent years, the emergence of blockchain technology (BT) has become a unique, most
disruptive, and trending technology. The decentralized database in BT emphasizes data …

Windows PE malware detection using ensemble learning

NA Azeez, OE Odufuwa, S Misra, J Oluranti… - Informatics, 2021 - mdpi.com
In this Internet age, there are increasingly many threats to the security and safety of users
daily. One of such threats is malicious software otherwise known as malware (ransomware …

A Comprehensive Analysis of Explainable AI for Malware Hunting

M Saqib, S Mahdavifar, BCM Fung… - ACM Computing …, 2024 - dl.acm.org
In the past decade, the number of malware variants has increased rapidly. Many
researchers have proposed to detect malware using intelligent techniques, such as Machine …

A holistic review of machine learning adversarial attacks in IoT networks

H Khazane, M Ridouani, F Salahdine, N Kaabouch - Future Internet, 2024 - mdpi.com
With the rapid advancements and notable achievements across various application
domains, Machine Learning (ML) has become a vital element within the Internet of Things …

Boosting training for PDF malware classifier via active learning

Y Li, X Wang, Z Shi, R Zhang, J Xue… - International journal of …, 2022 - Wiley Online Library
Abstract Machine learning algorithms are widely used for cybersecurity applications, include
spam, malware detection. In these applications, the machine learning model has to face …

A novel blockchain federated safety-as-a-service scheme for industrial IoT using machine learning

N Hasan, K Chaudhary, M Alam - Multimedia Tools and Applications, 2022 - Springer
Blockchains are costly in terms of computing and involve high overhead bandwidth and
delays that are not suitable for smart appliances. Enhancing the precision of output, quality …

Analysis of fileless malware and its evasive behavior

A Afreen, M Aslam, S Ahmed - 2020 International Conference …, 2020 - ieeexplore.ieee.org
Malware is any software that causes harm to the user information, computer systems or
network. Modern computing and internet systems are facing increase in malware threats …

Evaluation of local security event management system vs. standard antivirus software

A Pérez-Sánchez, R Palacios - Applied Sciences, 2022 - mdpi.com
Featured Application This work can be applied to develop new anti-malware strategies
based on event analysis. Abstract The detection and classification of threats in computer …