A comprehensive survey on machine learning approaches for malware detection in IoT-based enterprise information system
A Gaurav, BB Gupta, PK Panigrahi - Enterprise Information …, 2023 - Taylor & Francis
ABSTRACT The Internet of Things (IoT) is a relatively new technology that has piqued
academics' and business information systems' attention in recent years. The Internet of …
academics' and business information systems' attention in recent years. The Internet of …
[HTML][HTML] The rise of machine learning for detection and classification of malware: Research developments, trends and challenges
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 …
with the complexity of malware changing as quickly as innovation grows. Current state-of-the …
A survey on machine learning techniques for cyber security in the last decade
Pervasive growth and usage of the Internet and mobile applications have expanded
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …
A novel deep learning-based approach for malware detection
Malware detection approaches can be classified into two classes, including static analysis
and dynamic analysis. Conventional approaches of the two classes have their respective …
and dynamic analysis. Conventional approaches of the two classes have their respective …
A systematic review on imbalanced data challenges in machine learning: Applications and solutions
In machine learning, the data imbalance imposes challenges to perform data analytics in
almost all areas of real-world research. The raw primary data often suffers from the skewed …
almost all areas of real-world research. The raw primary data often suffers from the skewed …
Image-Based malware classification using ensemble of CNN architectures (IMCEC)
Both researchers and malware authors have demonstrated that malware scanners are
unfortunately limited and are easily evaded by simple obfuscation techniques. This paper …
unfortunately limited and are easily evaded by simple obfuscation techniques. This paper …
A survey on machine learning-based malware detection in executable files
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 …
done. Nowadays, cybercriminals (attacker) use malware as a weapon to carry out the …
Robust malware detection for internet of (battlefield) things devices using deep eigenspace learning
A Azmoodeh, A Dehghantanha… - IEEE transactions on …, 2018 - ieeexplore.ieee.org
Internet of Things (IoT) in military settings generally consists of a diverse range of Internet-
connected devices and nodes (eg, medical devices and wearable combat uniforms). These …
connected devices and nodes (eg, medical devices and wearable combat uniforms). These …
[HTML][HTML] Performance comparison and current challenges of using machine learning techniques in cybersecurity
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 …
world is becoming more and more dependent on the internet for everyday living. The …
MCFT-CNN: Malware classification with fine-tune convolution neural networks using traditional and transfer learning in Internet of Things
S Kumar - Future Generation Computer Systems, 2021 - Elsevier
With ever-increasing, internet-connected devices provide an opportunity to fulfil the
attacker's malicious intention. They use malicious programs to compromise the devices and …
attacker's malicious intention. They use malicious programs to compromise the devices and …