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[HTML][HTML] Malware detection issues, challenges, and future directions: A survey
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 …
increased the probability of corrupting data, stealing information, or other cybercrimes by …
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 …
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 …
Machine learning algorithm for malware detection: Taxonomy, current challenges, and future directions
Malware has emerged as a cyber security threat that continuously changes to target
computer systems, smart devices, and extensive networks with the development of …
computer systems, smart devices, and extensive networks with the development of …
Malware detection using machine learning algorithms for windows platform
Windows is a popular Graphical User Interface-based Operating System that provides
services like storage, run third-party software, play videos, network connection, etc. The …
services like storage, run third-party software, play videos, network connection, etc. The …
Features engineering to differentiate between malware and legitimate software
Malware is the primary attack vector against the modern enterprise. Therefore, it is crucial for
businesses to exclude malware from their computer systems. The most responsive solution …
businesses to exclude malware from their computer systems. The most responsive solution …
Malware Detection With Subspace Learning-Based One-Class Classification
Detecting malware is crucial for ensuring the security of computer systems. Traditional
machine learning models face challenges in effectively detecting malware, mainly due to the …
machine learning models face challenges in effectively detecting malware, mainly due to the …
Hyperparameter Tuning Menggunakan GridsearchCV pada Random Forest untuk Deteksi Malware
IMM Matin - MULTINETICS, 2023 - jurnal.pnj.ac.id
Random forest is one of the popular machine learning algorithms used for classification
tasks. In malware detection tasks, random forest can help identify malware with good …
tasks. In malware detection tasks, random forest can help identify malware with good …
A framework for collecting and analysis PE malware using modern honey network (MHN)
Nowadays, Windows is an operating system that is very popular among people, especially
users who have limited knowledge of computers. But unconsciously, the security threat to …
users who have limited knowledge of computers. But unconsciously, the security threat to …
[HTML][HTML] Lightweight and robust malware detection using dictionaries of api calls
Malware in today's business world has become a powerful tool used by cyber attackers. It
has become more advanced, spreading quickly and causing significant harm. Modern …
has become more advanced, spreading quickly and causing significant harm. Modern …