Revolutionizing cyber threat detection with large language models
Natural Language Processing (NLP) domain is experiencing a revolution due to the
capabilities of Pre-trained Large Language Models (LLMs), fueled by ground-breaking …
capabilities of Pre-trained Large Language Models (LLMs), fueled by ground-breaking …
[HTML][HTML] Security of federated learning with IoT systems: Issues, limitations, challenges, and solutions
Abstract Federated Learning (FL, or Collaborative Learning (CL)) has surely gained a
reputation for not only building Machine Learning (ML) models that rely on distributed …
reputation for not only building Machine Learning (ML) models that rely on distributed …
Advances in deep learning intrusion detection over encrypted data with privacy preservation: a systematic review
Many sensitive applications require that data remain confidential and undisclosed, even for
intrusion detection objectives. For this purpose, the detection of anomalies in encrypted data …
intrusion detection objectives. For this purpose, the detection of anomalies in encrypted data …
Network intrusion detection and mitigation in SDN using deep learning models
M Maddu, YN Rao - International Journal of Information Security, 2024 - Springer
Abstract Software-Defined Networking (SDN) is a contemporary network strategy utilized
instead of a traditional network structure. It provides significantly more administrative …
instead of a traditional network structure. It provides significantly more administrative …
Review on Approaches of Federated Modeling in Anomaly-Based Intrusion Detection for IoT Devices
The novelty of Federated Learning (FL) has emerged as a promising alternative to
centralized machine learning systems in the context of anomaly-based intrusion detection …
centralized machine learning systems in the context of anomaly-based intrusion detection …
Cyberattack defense mechanism using deep learning techniques in software-defined networks
DS Rao, AJ Emerson - International Journal of Information Security, 2024 - Springer
Software-defined networking (SDN) is a network architecture. It is becoming more popular
due to its centralized network administration, adaptability, and speed. However, the …
due to its centralized network administration, adaptability, and speed. However, the …
[HTML][HTML] Deep Neural Decision Forest (DNDF): A Novel Approach for Enhancing Intrusion Detection Systems in Network Traffic Analysis
Intrusion detection systems, also known as IDSs, are widely regarded as one of the most
essential components of an organization's network security. This is because IDSs serve as …
essential components of an organization's network security. This is because IDSs serve as …
BRL-ETDM: Bayesian reinforcement learning-based explainable threat detection model for industry 5.0 network
To enhance the universal adaptability of the Real-Time deployment of Industry 5.0, various
machine learning-based cyber threat detection models are given in the literature. Most of the …
machine learning-based cyber threat detection models are given in the literature. Most of the …
Revolutionizing Cyber Threat Detection with Large Language Models: A privacy-preserving BERT-based Lightweight Model for IoT/IIoT Devices
The field of Natural Language Processing (NLP) is currently undergoing a revolutionary
transformation driven by the power of pre-trained Large Language Models (LLMs) based on …
transformation driven by the power of pre-trained Large Language Models (LLMs) based on …
Federated Deep Learning for Intrusion Detection in Consumer-Centric Internet of Things
Consumer-centric Internet of Things (CIoT) will play a pivotal role in the fifth industrial
revolution (Industry 5.0) but it exhibits vulnerabilities that can render it susceptible to various …
revolution (Industry 5.0) but it exhibits vulnerabilities that can render it susceptible to various …