Internet of things: Security and solutions survey
The overwhelming acceptance and growing need for Internet of Things (IoT) products in
each aspect of everyday living is creating a promising prospect for the involvement of …
each aspect of everyday living is creating a promising prospect for the involvement of …
Artificial intelligence applications and self-learning 6G networks for smart cities digital ecosystems: Taxonomy, challenges, and future directions
The recent upsurge of smart cities' applications and their building blocks in terms of the
Internet of Things (IoT), Artificial Intelligence (AI), federated and distributed learning, big data …
Internet of Things (IoT), Artificial Intelligence (AI), federated and distributed learning, big data …
Federated deep learning for zero-day botnet attack detection in IoT-edge devices
Deep learning (DL) has been widely proposed for botnet attack detection in Internet of
Things (IoT) networks. However, the traditional centralized DL (CDL) method cannot be …
Things (IoT) networks. However, the traditional centralized DL (CDL) method cannot be …
[HTML][HTML] DCNNBiLSTM: An efficient hybrid deep learning-based intrusion detection system
In recent years, all real-world processes have been shifted to the cyber environment
practically, and computers communicate with one another over the Internet. As a result, there …
practically, and computers communicate with one another over the Internet. As a result, there …
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 …
A novel intrusion detection method based on lightweight neural network for internet of things
The purpose of a network intrusion detection (NID) is to detect intrusions in the network,
which plays a critical role in ensuring the security of the Internet of Things (IoT). Recently …
which plays a critical role in ensuring the security of the Internet of Things (IoT). Recently …
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) …
Semisupervised federated-learning-based intrusion detection method for internet of things
Federated learning (FL) has become an increasingly popular solution for intrusion detection
to avoid data privacy leakage in Internet of Things (IoT) edge devices. Existing FL-based …
to avoid data privacy leakage in Internet of Things (IoT) edge devices. Existing FL-based …
GAN augmentation to deal with imbalance in imaging-based intrusion detection
Nowadays attacks on computer networks continue to advance at a rate outpacing cyber
defenders' ability to write new attack signatures. This paper illustrates a deep learning …
defenders' ability to write new attack signatures. This paper illustrates a deep learning …
Semi-supervised specific emitter identification method using metric-adversarial training
Specific emitter identification (SEI) plays an increasingly crucial and potential role in both
military and civilian scenarios. It refers to a process to discriminate individual emitters from …
military and civilian scenarios. It refers to a process to discriminate individual emitters from …