Efficient classification of enciphered SCADA network traffic in smart factory using decision tree algorithm

LAC Ahakonye, CI Nwakanma, JM Lee, DS Kim - IEEE Access, 2021 - ieeexplore.ieee.org
Vulnerability detection in Supervisory Control and Data Acquisition (SCADA) network of a
Smart Factory (SF) is a high-priority research area in the cyber-security domain. Choosing …

An explainable efficient flow-based Industrial IoT intrusion detection system

MM Alani - Computers and Electrical Engineering, 2023 - Elsevier
With the steady growth in the adoption of IoT in an industrial context, security challenges
intensify. Security threats to IoT devices in a nuclear plant or an oil refinery are much higher …

DeepIIoT: An explainable deep learning based intrusion detection system for industrial IOT

MM Alani, E Damiani, U Ghosh - 2022 IEEE 42nd International …, 2022 - ieeexplore.ieee.org
IoT adoption is becoming widespread in different areas of applications in our daily lives. The
increased reliance on IoT devices has made them a worthy target for attackers. With …

Intrusion detection systems trends to counteract growing cyber-attacks on cyber-physical systems

J Ali - 2021 22nd International Arab Conference on …, 2021 - ieeexplore.ieee.org
Cyber-Physical Systems (CPS) suffer from extendable vulnerabilities due to the
convergence of the physical world with the cyber world, which makes it victim to a number of …

Classification and characterization of encoded traffic in SCADA network using hybrid deep learning scheme

LAC Ahakonye, GC Amaizu… - Journal of …, 2024 - ieeexplore.ieee.org
The domain name system (DNS) has evolved into an essential component of network
communications, as well as a critical component of critical industrial systems (CIS) and …

Enhancing intrusion detection in IIoT: optimized CNN model with multi-class SMOTE balancing

AM Eid, B Soudan, AB Nassif, MN Injadat - Neural Computing and …, 2024 - Springer
This work introduces an intrusion detection system (IDS) tailored for industrial internet of
things (IIoT) environments based on an optimized convolutional neural network (CNN) …

AOC-IDS: Autonomous Online Framework with Contrastive Learning for Intrusion Detection

X Zhang, R Zhao, Z Jiang, Z Sun, Y Ding… - arxiv preprint arxiv …, 2024 - arxiv.org
The rapid expansion of the Internet of Things (IoT) has raised increasing concern about
targeted cyber attacks. Previous research primarily focused on static Intrusion Detection …

[PDF][PDF] RRCNN: Request Response-Based Convolutional Neural Network for ICS Network Traffic Anomaly Detection

Y Du, S Zhang, G Wan, D Zhou, J Lu… - Comput. Mater …, 2023 - cdn.techscience.cn
Nowadays, industrial control system (ICS) has begun to integrate with the Internet. While the
Internet has brought convenience to ICS, it has also brought severe security concerns …

Interrelation between Temporal Coordinates and Intrusion Detection Techniques in Cyber Physical Systems

S Jacob, G Balanagireddy, KS Kumar… - 2022 International …, 2022 - ieeexplore.ieee.org
Network traffic and its temporal coordinates of flow are affected by factors such as traffic
volume, peak or low usage times, and available resource bandwidth. The problem of …

Otkrivanje anomalija mrežnog prometa metodom klasifikacije strojnim učenjem u hibridnoj programski definiranoj mreži

I Fosić - 2024 - dr.nsk.hr
Sažetak Disertacija predstavlja inovativan pristup kibernetičkoj sigurnosti u kontekstu
hibridnih programski definiranih mreža (SDN), s naglaskom na integraciju tehnika strojnog …