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 …
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 developing 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 …
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 …
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 …
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 …
A multimodal deep learning method for android malware detection using various features
With the widespread use of smartphones, the number of malware has been increasing
exponentially. Among smart devices, android devices are the most targeted devices by …
exponentially. Among smart devices, android devices are the most targeted devices by …
The relationship between trust in AI and trustworthy machine learning technologies
To design and develop AI-based systems that users and the larger public can justifiably
trust, one needs to understand how machine learning technologies impact trust. To guide …
trust, one needs to understand how machine learning technologies impact trust. To guide …
Why do adversarial attacks transfer? explaining transferability of evasion and poisoning attacks
Transferability captures the ability of an attack against a machine-learning model to be
effective against a different, potentially unknown, model. Empirical evidence for …
effective against a different, potentially unknown, model. Empirical evidence for …
Intriguing properties of adversarial ml attacks in the problem space
Recent research efforts on adversarial ML have investigated problem-space attacks,
focusing on the generation of real evasive objects in domains where, unlike images, there is …
focusing on the generation of real evasive objects in domains where, unlike images, there is …
A deep recurrent neural network based approach for internet of things malware threat hunting
Abstract Internet of Things (IoT) devices are increasingly deployed in different industries and
for different purposes (eg sensing/collecting of environmental data in both civilian and …
for different purposes (eg sensing/collecting of environmental data in both civilian and …