[HTML][HTML] The rise of machine learning for detection and classification of malware: Research developments, trends and challenges

D Gibert, C Mateu, J Planes - Journal of Network and Computer …, 2020 - Elsevier
The struggle between security analysts and malware developers is a never-ending battle
with the complexity of malware changing as quickly as innovation grows. Current state-of-the …

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 on machine learning techniques for cyber security in the last decade

K Shaukat, S Luo, V Varadharajan, IA Hameed… - IEEE …, 2020 - ieeexplore.ieee.org
Pervasive growth and usage of the Internet and mobile applications have expanded
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …

A state-of-the-art survey of malware detection approaches using data mining techniques

A Souri, R Hosseini - Human-centric Computing and Information Sciences, 2018 - Springer
Data mining techniques have been concentrated for malware detection in the recent
decade. The battle between security analyzers and malware scholars is everlasting as …

Ransomware threat success factors, taxonomy, and countermeasures: A survey and research directions

BAS Al-Rimy, MA Maarof, SZM Shaid - Computers & Security, 2018 - Elsevier
Ransomware is a malware category that exploits security mechanisms such as cryptography
in order to hijack user files and related resources and demands money in exchange for the …

Performance comparison and current challenges of using machine learning techniques in cybersecurity

K Shaukat, S Luo, V Varadharajan, IA Hameed, S Chen… - Energies, 2020 - mdpi.com
Cyberspace has become an indispensable factor for all areas of the modern world. The
world is becoming more and more dependent on the internet for everyday living. The …

Droidcat: Effective android malware detection and categorization via app-level profiling

H Cai, N Meng, B Ryder, D Yao - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Most existing Android malware detection and categorization techniques are static
approaches, which suffer from evasion attacks, such as obfuscation. By analyzing program …

Advanced persistent threats (apt): evolution, anatomy, attribution and countermeasures

A Sharma, BB Gupta, AK Singh… - Journal of Ambient …, 2023 - Springer
In today's cyber warfare realm, every stakeholder in cyberspace is becoming more potent by
developing advanced cyber weapons. They have equipped with the most advanced …

Cyberattacks detection in iot-based smart city applications using machine learning techniques

MM Rashid, J Kamruzzaman, MM Hassan… - International Journal of …, 2020 - mdpi.com
In recent years, the widespread deployment of the Internet of Things (IoT) applications has
contributed to the development of smart cities. A smart city utilizes IoT-enabled technologies …

Dynamic analysis for IoT malware detection with convolution neural network model

J Jeon, JH Park, YS Jeong - Ieee Access, 2020 - ieeexplore.ieee.org
Internet of Things (IoT) technology provides the basic infrastructure for a hyper connected
society where all things are connected and exchange information through the Internet. IoT …