Network intrusion detection for IoT security based on learning techniques
Pervasive growth of Internet of Things (IoT) is visible across the globe. The 2016 Dyn
cyberattack exposed the critical fault-lines among smart networks. Security of IoT has …
cyberattack exposed the critical fault-lines among smart networks. Security of IoT has …
A detailed investigation and analysis of using machine learning techniques for intrusion detection
Intrusion detection is one of the important security problems in todays cyber world. A
significant number of techniques have been developed which are based on machine …
significant number of techniques have been developed which are based on machine …
A survey on security challenges in cloud computing: issues, threats, and solutions
Cloud computing has gained huge attention over the past decades because of continuously
increasing demands. There are several advantages to organizations moving toward cloud …
increasing demands. There are several advantages to organizations moving toward cloud …
Intrusion detection systems for IoT-based smart environments: a survey
One of the goals of smart environments is to improve the quality of human life in terms of
comfort and efficiency. The Internet of Things (IoT) paradigm has recently evolved into a …
comfort and efficiency. The Internet of Things (IoT) paradigm has recently evolved into a …
Intrusion detection system for IoT based on deep learning and modified reptile search algorithm
This study proposes a novel framework to improve intrusion detection system (IDS)
performance based on the data collected from the Internet of things (IoT) environments. The …
performance based on the data collected from the Internet of things (IoT) environments. The …
A comprehensive survey on security challenges in different network layers in cloud computing
Conducting enterprise distributed computing and providing facilities such as data storage
and resource sharing, along with the provision of cheap, easy, and flexible services, have …
and resource sharing, along with the provision of cheap, easy, and flexible services, have …
A hybrid deep learning-based model for anomaly detection in cloud datacenter networks
With the emergence of the Internet-of-Things (IoT) and seamless Internet connectivity, the
need to process streaming data on real-time basis has become essential. However, the …
need to process streaming data on real-time basis has become essential. However, the …
IoT intrusion detection system using deep learning and enhanced transient search optimization
The great advancements in communication, cloud computing, and the internet of things (IoT)
have opened critical challenges in security. With these developments, cyberattacks are also …
have opened critical challenges in security. With these developments, cyberattacks are also …
Autoencoder-based feature learning for cyber security applications
M Yousefi-Azar, V Varadharajan… - … joint conference on …, 2017 - ieeexplore.ieee.org
This paper presents a novel feature learning model for cyber security tasks. We propose to
use Auto-encoders (AEs), as a generative model, to learn latent representation of different …
use Auto-encoders (AEs), as a generative model, to learn latent representation of different …
Computational intelligence intrusion detection techniques in mobile cloud computing environments: Review, taxonomy, and open research issues
With the increasing utilization of the Internet and its provided services, an increase in cyber-
attacks to exploit the information occurs. A technology to store and maintain user's …
attacks to exploit the information occurs. A technology to store and maintain user's …