Deep transfer learning for intrusion detection in industrial control networks: A comprehensive review
Globally, the external internet is increasingly being connected to industrial control systems.
As a result, there is an immediate need to protect these networks from a variety of threats …
As a result, there is an immediate need to protect these networks from a variety of threats …
[PDF][PDF] Deep transfer learning applications in intrusion detection systems: A comprehensive review
Globally, the external Internet is increasingly being connected to the contemporary industrial
control system. As a result, there is an immediate need to protect the network from several …
control system. As a result, there is an immediate need to protect the network from several …
[HTML][HTML] Flowtransformer: A transformer framework for flow-based network intrusion detection systems
This paper presents the FlowTransformer framework, a novel approach for implementing
transformer-based Network Intrusion Detection Systems (NIDSs). FlowTransformer …
transformer-based Network Intrusion Detection Systems (NIDSs). FlowTransformer …
Evaluation of machine learning techniques for traffic flow-based intrusion detection
Cybersecurity is one of the great challenges of today's world. Rapid technological
development has allowed society to prosper and improve the quality of life and the world is …
development has allowed society to prosper and improve the quality of life and the world is …
[HTML][HTML] An automatic complex event processing rules generation system for the recognition of real-time IoT attack patterns
J Roldán-Gómez, J Boubeta-Puig… - … Applications of Artificial …, 2023 - Elsevier
Abstract The Internet of Things (IoT) has grown rapidly to become the core of many areas of
application, leading to the integration of sensors, with IoT devices. However, the number of …
application, leading to the integration of sensors, with IoT devices. However, the number of …
Toward detecting cyberattacks targeting modern power grids: A deep learning framework
Modern power and energy networks include a plethora of distributed control and monitoring
equipment, exchanging data through information and communication technology (ICT) …
equipment, exchanging data through information and communication technology (ICT) …
Anomaly based intrusion detection model using supervised machine learning techniques
An intrusion detection system (IDS) is a software system that keeps track of network traffic
and looks for anomalies. Abnormal or unusual network changes could be signs of fraud at …
and looks for anomalies. Abnormal or unusual network changes could be signs of fraud at …
Cybersecurity in smart cities: Detection of opposing decisions on anomalies in the computer network behavior
The increased use of urban technologies in smart cities brings new challenges and issues.
Cyber security has become increasingly important as many critical components of …
Cyber security has become increasingly important as many critical components of …
Detecting cyber threats with a Graph-Based NIDPS
BOT Wen, N Syahriza, NCW Xian, NG Wei… - … Measures for Logistics …, 2024 - igi-global.com
This chapter explores the topic of a novel network-based intrusion detection system (NIDPS)
that utilises the concept of graph theory to detect and prevent incoming threats. With …
that utilises the concept of graph theory to detect and prevent incoming threats. With …
Intrusion detection systems for IoT based on bio-inspired and machine learning techniques: a systematic review of the literature
Recent technological advancements have significantly expanded both networks and data,
thereby introducing new forms of attacks that pose considerable challenges to intrusion …
thereby introducing new forms of attacks that pose considerable challenges to intrusion …