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 …
harmful threats to the digital world. Malware mitigation techniques have evolved over the …
Cybersecurity data science: an overview from machine learning perspective
In a computing context, cybersecurity is undergoing massive shifts in technology and its
operations in recent days, and data science is driving the change. Extracting security …
operations in recent days, and data science is driving the change. Extracting security …
Robust intelligent malware detection using deep learning
R Vinayakumar, M Alazab, KP Soman… - IEEE …, 2019 - ieeexplore.ieee.org
Security breaches due to attacks by malicious software (malware) continue to escalate
posing a major security concern in this digital age. With many computer users, corporations …
posing a major security concern in this digital age. With many computer users, corporations …
Deep learning based Sequential model for malware analysis using Windows exe API Calls
Malware development has seen diversity in terms of architecture and features. This
advancement in the competencies of malware poses a severe threat and opens new …
advancement in the competencies of malware poses a severe threat and opens new …
[PDF][PDF] A survey on malware analysis techniques: Static, dynamic, hybrid and memory analysis
The threats malware pose to the people around the world are increasing rapidly. A software
that sneaks to your computer system without your knowledge with a harmful intent to disrupt …
that sneaks to your computer system without your knowledge with a harmful intent to disrupt …
API-MalDetect: Automated malware detection framework for windows based on API calls and deep learning techniques
This paper presents API-MalDetect, a new deep learning-based automated framework for
detecting malware attacks in Windows systems. The framework uses an NLP-based encoder …
detecting malware attacks in Windows systems. The framework uses an NLP-based encoder …
An adaptive multi-layer botnet detection technique using machine learning classifiers
In recent years, the botnets have been the most common threats to network security since it
exploits multiple malicious codes like a worm, Trojans, Rootkit, etc. The botnets have been …
exploits multiple malicious codes like a worm, Trojans, Rootkit, etc. The botnets have been …
A method for windows malware detection based on deep learning
X Huang, L Ma, W Yang, Y Zhong - Journal of Signal Processing Systems, 2021 - Springer
As the Internet rapidly develops, the types and quantity of malware continue to diversify and
increase, and the technology of evading security software is becoming more and more …
increase, and the technology of evading security software is becoming more and more …
[PDF][PDF] Zero-day Malware Detection based on Supervised Learning Algorithms of API call Signatures.
Zero-day or unknown malware are created using code obfuscation techniques that can
modify the parent code to produce offspring copies which have the same functionality but …
modify the parent code to produce offspring copies which have the same functionality but …
Profiling and classifying the behavior of malicious codes
M Alazab - Journal of Systems and Software, 2015 - Elsevier
Malware is a major security threat confronting computer systems and networks and has
increased in scale and impact from the early days of ICT. Traditional protection mechanisms …
increased in scale and impact from the early days of ICT. Traditional protection mechanisms …