Internet of things (iot) security intelligence: a comprehensive overview, machine learning solutions and research directions
Abstract The Internet of Things (IoT) is one of the most widely used technologies today, and
it has a significant effect on our lives in a variety of ways, including social, commercial, and …
it has a significant effect on our lives in a variety of ways, including social, commercial, and …
Machine learning for intelligent data analysis and automation in cybersecurity: current and future prospects
IH Sarker - Annals of Data Science, 2023 - Springer
Due to the digitization and Internet of Things revolutions, the present electronic world has a
wealth of cybersecurity data. Efficiently resolving cyber anomalies and attacks is becoming a …
wealth of cybersecurity data. Efficiently resolving cyber anomalies and attacks is becoming a …
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 …
A survey of android malware detection with deep neural models
Deep Learning (DL) is a disruptive technology that has changed the landscape of cyber
security research. Deep learning models have many advantages over traditional Machine …
security research. Deep learning models have many advantages over traditional Machine …
A review on machine learning and deep learning perspectives of IDS for IoT: recent updates, security issues, and challenges
Abstract Internet of Things (IoT) is widely accepted technology in both industrial as well as
academic field. The objective of IoT is to combine the physical environment with the cyber …
academic field. The objective of IoT is to combine the physical environment with the cyber …
Deep learning for anomaly detection: A survey
R Chalapathy, S Chawla - arXiv preprint arXiv:1901.03407, 2019 - arxiv.org
Anomaly detection is an important problem that has been well-studied within diverse
research areas and application domains. The aim of this survey is two-fold, firstly we present …
research areas and application domains. The aim of this survey is two-fold, firstly we present …
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 …
A survey of machine and deep learning methods for internet of things (IoT) security
The Internet of Things (IoT) integrates billions of smart devices that can communicate with
one another with minimal human intervention. IoT is one of the fastest developing fields in …
one another with minimal human intervention. IoT is one of the fastest developing fields in …
[HTML][HTML] DL-Droid: Deep learning based android malware detection using real devices
The Android operating system has been the most popular for smartphones and tablets since
2012. This popularity has led to a rapid raise of Android malware in recent years. The …
2012. This popularity has led to a rapid raise of Android malware in recent years. The …
A survey of deep learning methods for cyber security
DS Berman, AL Buczak, JS Chavis, CL Corbett - Information, 2019 - mdpi.com
This survey paper describes a literature review of deep learning (DL) methods for cyber
security applications. A short tutorial-style description of each DL method is provided …
security applications. A short tutorial-style description of each DL method is provided …