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 …
Static analysis of information systems for IoT cyber security: a survey of machine learning approaches
Ensuring security for modern IoT systems requires the use of complex methods to analyze
their software. One of the most in-demand methods that has repeatedly been proven to be …
their software. One of the most in-demand methods that has repeatedly been proven to be …
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 …
[HTML][HTML] Ransomware detection using random forest technique
BM Khammas - ICT Express, 2020 - Elsevier
Nowadays, the ransomware became a serious threat challenge the computing world that
requires an immediate consideration to avoid financial and moral blackmail. So, there is a …
requires an immediate consideration to avoid financial and moral blackmail. So, there is a …
An investigation into the performances of the state-of-the-art machine learning approaches for various cyber-attack detection: A survey
In this research, we analyzed the suitability of each of the current state-of-the-art machine
learning models for various cyberattack detection from the past 5 years with a major …
learning models for various cyberattack detection from the past 5 years with a major …
Combining multiple feature-ranking techniques and clustering of variables for feature selection
Feature selection aims to eliminate redundant or irrelevant variables from input data to
reduce computational cost, provide a better understanding of data and improve prediction …
reduce computational cost, provide a better understanding of data and improve prediction …
Feature selection using a machine learning to classify a malware
M Al-Kasassbeh, S Mohammed, M Alauthman… - Handbook of Computer …, 2020 - Springer
Generally, malware has come to be known as one of the biggest threats, so malware is a
program which operates malicious actions and steals information, to specifically identify it as …
program which operates malicious actions and steals information, to specifically identify it as …
Leveraging support vector machine for opcode density based detection of crypto-ransomware
J Baldwin, A Dehghantanha - Cyber threat intelligence, 2018 - Springer
Ransomware is a significant global threat, with easy deployment due to the prevalent
ransomware-as-a-service model. Machine learning algorithms incorporating the use of …
ransomware-as-a-service model. Machine learning algorithms incorporating the use of …
Malware detection based on opcode frequency
A Yewale, M Singh - 2016 International Conference on …, 2016 - ieeexplore.ieee.org
Malware is a computer program or a piece of software that is designed to penetrate and
detriment computers without owner's permission. There are different malware types such as …
detriment computers without owner's permission. There are different malware types such as …
Transformer oil quality assessment using random forest with feature engineering
MEA Senoussaoui, M Brahami, I Fofana - Energies, 2021 - mdpi.com
Machine learning is widely used as a panacea in many engineering applications including
the condition assessment of power transformers. Most statistics attribute the main cause of …
the condition assessment of power transformers. Most statistics attribute the main cause of …