Fed-anids: Federated learning for anomaly-based network intrusion detection systems
As computer networks and interconnected systems continue to gain widespread adoption,
ensuring cybersecurity has become a prominent concern for organizations, regardless of …
ensuring cybersecurity has become a prominent concern for organizations, regardless of …
A one-dimensional convolutional neural network (1D-CNN) based deep learning system for network intrusion detection
The connectivity of devices through the internet plays a remarkable role in our daily lives.
Many network-based applications are utilized in different domains, eg, health care, smart …
Many network-based applications are utilized in different domains, eg, health care, smart …
Intrusion Detection based on Federated Learning: a systematic review
JL Hernandez-Ramos, G Karopoulos… - arXiv preprint arXiv …, 2023 - arxiv.org
The evolution of cybersecurity is undoubtedly associated and intertwined with the
development and improvement of artificial intelligence (AI). As a key tool for realizing more …
development and improvement of artificial intelligence (AI). As a key tool for realizing more …
Federated learning based IDS approach for the IoV
A Hbaieb, S Ayed, L Chaari - … of the 17th international conference on …, 2022 - dl.acm.org
The Internet of Vehicles (IoV) is an Internet of Things (IoT) application that offers several
utilities such as traffic analysis, safe driving, road optimization, and travel comfort. Software …
utilities such as traffic analysis, safe driving, road optimization, and travel comfort. Software …
Аналитический обзор подходов к обнаружению вторжений, основанных на федеративном обучении: преимущества использования и открытые задачи
ЕС Новикова, ЕВ Федорченко, ИВ Котенко… - Информатика и …, 2023 - mathnet.ru
Для обеспечения точного и своевременного реагирования на различные типы атак
системы обнаружения вторжений собирают и анализируют большое количество …
системы обнаружения вторжений собирают и анализируют большое количество …
Enhancing anomaly detection in distributed power systems using autoencoder-based federated learning
The growing use of Internet-of-Things devices in electric power systems has resulted in
increased complexity and flexibility, making monitoring power usage critical for effective …
increased complexity and flexibility, making monitoring power usage critical for effective …
A Collaborative Software Defined Network-Based Smart Grid Intrusion Detection System
S Chatzimiltis, M Shojafar… - IEEE Open Journal …, 2024 - ieeexplore.ieee.org
Current technological advancements in Software Defined Networks (SDN) can provide
efficient solutions for smart grids (SGs). An SDN-based SG promises to enhance the …
efficient solutions for smart grids (SGs). An SDN-based SG promises to enhance the …
Efficient Privacy‐Preserving Federated Deep Learning for Network Intrusion of Industrial IoT
N He, Z Zhang, X Wang, T Gao - International Journal of …, 2023 - Wiley Online Library
Intrusion detection systems play a very important role in industrial Internet network security.
However, in the large‐scale, complex, and heterogeneous industrial Internet of Things (IoT) …
However, in the large‐scale, complex, and heterogeneous industrial Internet of Things (IoT) …
Botnet-based IoT Network Attacks Identification using LSTM
UB Clinton, N Hoque, KR Singh - 2023 14th International …, 2023 - ieeexplore.ieee.org
Internet of Things (IoT) networks are growing significantly as a modern communication
technology that changes the world tremendously, and the vulnerabilities of IoT have brought …
technology that changes the world tremendously, and the vulnerabilities of IoT have brought …
Federated learning-based intrusion detection on non-IID data
Intrusion detection is an effective means to deal with network attacks. Currently, the
commonly used detection methods are based on machine learning. However, traditional …
commonly used detection methods are based on machine learning. However, traditional …