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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 …
The role of machine learning in cybersecurity
Machine Learning (ML) represents a pivotal technology for current and future information
systems, and many domains already leverage the capabilities of ML. However, deployment …
systems, and many domains already leverage the capabilities of ML. However, deployment …
Dos and don'ts of machine learning in computer security
With the growing processing power of computing systems and the increasing availability of
massive datasets, machine learning algorithms have led to major breakthroughs in many …
massive datasets, machine learning algorithms have led to major breakthroughs in many …
“real attackers don't compute gradients”: bridging the gap between adversarial ml research and practice
Recent years have seen a proliferation of research on adversarial machine learning.
Numerous papers demonstrate powerful algorithmic attacks against a wide variety of …
Numerous papers demonstrate powerful algorithmic attacks against a wide variety of …
A review of android malware detection approaches based on machine learning
K Liu, S Xu, G Xu, M Zhang, D Sun, H Liu - IEEE access, 2020 - ieeexplore.ieee.org
Android applications are develo** rapidly across the mobile ecosystem, but Android
malware is also emerging in an endless stream. Many researchers have studied the …
malware is also emerging in an endless stream. Many researchers have studied the …
Wild patterns: Ten years after the rise of adversarial machine learning
Deep neural networks and machine-learning algorithms are pervasively used in several
applications, ranging from computer vision to computer security. In most of these …
applications, ranging from computer vision to computer security. In most of these …
Multimodal dual-embedding networks for malware open-set recognition
Malware open-set recognition (MOSR) is an emerging research domain that aims at jointly
classifying malware samples from known families and detecting the ones from novel …
classifying malware samples from known families and detecting the ones from novel …
Unique identification of 50,000+ virtual reality users from head & hand motion data
With the recent explosive growth of interest and investment in virtual reality (VR) and the so-
called" metaverse," public attention has rightly shifted toward the unique security and privacy …
called" metaverse," public attention has rightly shifted toward the unique security and privacy …
Machine learning in cybersecurity: a comprehensive survey
Today's world is highly network interconnected owing to the pervasiveness of small personal
devices (eg, smartphones) as well as large computing devices or services (eg, cloud …
devices (eg, smartphones) as well as large computing devices or services (eg, cloud …