Deep learning approaches for detecting DDoS attacks: A systematic review
In today's world, technology has become an inevitable part of human life. In fact, during the
Covid-19 pandemic, everything from the corporate world to educational institutes has shifted …
Covid-19 pandemic, everything from the corporate world to educational institutes has shifted …
Machine learning techniques to detect a DDoS attack in SDN: A systematic review
The recent advancements in security approaches have significantly increased the ability to
identify and mitigate any type of threat or attack in any network infrastructure, such as a …
identify and mitigate any type of threat or attack in any network infrastructure, such as a …
Boosting-based DDoS detection in internet of things systems
I Cvitić, D Perakovic, BB Gupta… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Distributed Denial-of-Service (DDoS) attacks remain challenging to mitigate in the existing
systems, including in-home networks that comprise different Internet of Things (IoT) devices …
systems, including in-home networks that comprise different Internet of Things (IoT) devices …
A framework for malicious traffic detection in IoT healthcare environment
The Internet of things (IoT) has emerged as a topic of intense interest among the research
and industrial community as it has had a revolutionary impact on human life. The rapid …
and industrial community as it has had a revolutionary impact on human life. The rapid …
A new DDoS attacks intrusion detection model based on deep learning for cybersecurity
The data is exposed to many attacks during communication in the network environment. It is
becoming increasingly essential to identify intrusions into network communications …
becoming increasingly essential to identify intrusions into network communications …
An optimized CNN-based intrusion detection system for reducing risks in smart farming
Smart farming is a well-known and superior method of managing a farm, becoming more
prevalent in today's contemporary agricultural practices. Crops are monitored for their …
prevalent in today's contemporary agricultural practices. Crops are monitored for their …
A comprehensive review of vulnerabilities and AI-enabled defense against DDoS attacks for securing cloud services
The advent of cloud computing has made a global impact by providing on-demand services,
elasticity, scalability, and flexibility, hence delivering cost-effective resources to end users in …
elasticity, scalability, and flexibility, hence delivering cost-effective resources to end users in …
Intrusion detection in internet of things systems: a review on design approaches leveraging multi-access edge computing, machine learning, and datasets
The explosive growth of the Internet of Things (IoT) applications has imposed a dramatic
increase of network data and placed a high computation complexity across various …
increase of network data and placed a high computation complexity across various …
A two-fold machine learning approach to prevent and detect IoT botnet attacks
The botnet attack is a multi-stage and the most prevalent cyber-attack in the Internet of
Things (IoT) environment that initiates with scanning activity and ends at the distributed …
Things (IoT) environment that initiates with scanning activity and ends at the distributed …
Transfer learning approach to IDS on cloud IoT devices using optimized CNN
Data centralization can potentially increase Internet of Things (IoT) usage. The trend is to
move IoT devices to a centralized server with higher memory capacity and a more robust …
move IoT devices to a centralized server with higher memory capacity and a more robust …