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AI-big data analytics for building automation and management systems: a survey, actual challenges and future perspectives
In theory, building automation and management systems (BAMSs) can provide all the
components and functionalities required for analyzing and operating buildings. However, in …
components and functionalities required for analyzing and operating buildings. However, in …
Internet of things (IoT) security dataset evolution: Challenges and future directions
The evolution of mobile technologies has introduced smarter and more connected objects
into our day-to-day lives. This trend, known as the Internet of Things (IoT), has applications …
into our day-to-day lives. This trend, known as the Internet of Things (IoT), has applications …
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 …
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 …
[HTML][HTML] Deep learning-based intrusion detection for distributed denial of service attack in agriculture 4.0
Smart Agriculture or Agricultural Internet of things, consists of integrating advanced
technologies (eg, NFV, SDN, 5G/6G, Blockchain, IoT, Fog, Edge, and AI) into existing farm …
technologies (eg, NFV, SDN, 5G/6G, Blockchain, IoT, Fog, Edge, and AI) into existing farm …
Performance evaluation of deep learning techniques for DoS attacks detection in wireless sensor network
Wireless sensor networks (WSNs) are increasingly being used for data monitoring and
collection purposes. Typically, they consist of a large number of sensor nodes that are used …
collection purposes. Typically, they consist of a large number of sensor nodes that are used …
Cyber security for detecting distributed denial of service attacks in agriculture 4.0: Deep learning model
Attackers are increasingly targeting Internet of Things (IoT) networks, which connect
industrial devices to the Internet. To construct network intrusion detection systems (NIDSs) …
industrial devices to the Internet. To construct network intrusion detection systems (NIDSs) …
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 …
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 …
Adversarial Deep Learning approach detection and defense against DDoS attacks in SDN environments
Over the last few years, Software Defined Networking (SDN) paradigm has become an
emerging architecture to design future networks and to meet new application demands. SDN …
emerging architecture to design future networks and to meet new application demands. SDN …