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 …
Recent advances in Internet of Things (IoT) infrastructures for building energy systems: A review
This paper summarises a literature review on the applications of Internet of Things (IoT) with
the aim of enhancing building energy use and reducing greenhouse gas emissions (GHGs) …
the aim of enhancing building energy use and reducing greenhouse gas emissions (GHGs) …
Internet of Things attack detection using hybrid Deep Learning Model
Abstract The Internet of Things (IoT) has become a very popular area of research due to its
large-scale implementation and challenges. However, security is the key concern while …
large-scale implementation and challenges. However, security is the key concern while …
A survey on internet of things security: Requirements, challenges, and solutions
Abstract Internet of Things (IoT) is one of the most promising technologies that aims to
enhance humans' quality of life (QoL). IoT plays a significant role in several fields such as …
enhance humans' quality of life (QoL). IoT plays a significant role in several fields such as …
Botnet Attack Detection by Using CNN‐LSTM Model for Internet of Things Applications
H Alkahtani, THH Aldhyani - Security and Communication …, 2021 - Wiley Online Library
The Internet of Things (IoT) has grown rapidly, and nowadays, it is exploited by cyber attacks
on IoT devices. An accurate system to identify malicious attacks on the IoT environment has …
on IoT devices. An accurate system to identify malicious attacks on the IoT environment has …
Deep neural network based anomaly detection in Internet of Things network traffic tracking for the applications of future smart cities
An anomaly exposure system's foremost objective is to categorize the behavior of the system
into normal and untruthful actions. To estimate the possible incidents, the administrators of …
into normal and untruthful actions. To estimate the possible incidents, the administrators of …
[PDF][PDF] 5G network simulation in smart cities using neural network algorithm
S Smys, H Wang, A Basar - Journal of Artificial Intelligence, 2021 - academia.edu
The speed of internet has increased dramatically with the introduction of 4G and 5G
promises an even greater transmission rate with coverage outdoors and indoors in smart …
promises an even greater transmission rate with coverage outdoors and indoors in smart …
Developing an efficient feature engineering and machine learning model for detecting IoT-botnet cyber attacks
M Panda, AM Abd Allah, AE Hassanien - IEEE Access, 2021 - ieeexplore.ieee.org
The proliferation of Internet of Things (IoT) systems and smart digital devices, has perceived
them targeted by network attacks. Botnets are vectors buttoned up which the attackers …
them targeted by network attacks. Botnets are vectors buttoned up which the attackers …
Ensemble learning methods for anomaly intrusion detection system in smart grid
Smart grid is an emerging technology that delivers intelligently to the end-users through two-
way communication. However, this technology can be subject to several cyber-attacks due …
way communication. However, this technology can be subject to several cyber-attacks due …
A graph neural network method for distributed anomaly detection in IoT
Recent IoT proliferation has undeniably affected the way organizational activities and
business procedures take place within several IoT domains such as smart manufacturing …
business procedures take place within several IoT domains such as smart manufacturing …