An improved autoencoder-based approach for anomaly detection in industrial control systems

MM Aslam, A Tufail, LC De Silva… - Systems Science & …, 2024 - Taylor & Francis
Security is a complex issue in critical infrastructure like industrial control systems (ICS) since
its leakages cause critical damage. Protecting the ICS environment from external threats …

[HTML][HTML] A survey and analysis of intrusion detection models based on cse-cic-ids2018 big data

JL Leevy, TM Khoshgoftaar - Journal of Big Data, 2020 - Springer
The exponential growth in computer networks and network applications worldwide has been
matched by a surge in cyberattacks. For this reason, datasets such as CSE-CIC-IDS2018 …

[PDF][PDF] Hybrid Multi-Objective Deep Learning Model for Anomaly Detection in Cloud Computing Environment

RR Palle - International Journal of Scientific Research in Science …, 2015 - academia.edu
Cloud computing environments play a pivotal role in the IT landscape, seamlessly integrated
into the fabric of organizations and individuals' daily activities. Despite the myriad …

Enhanced network anomaly detection based on deep neural networks

S Naseer, Y Saleem, S Khalid, MK Bashir, J Han… - IEEE …, 2018 - ieeexplore.ieee.org
Due to the monumental growth of Internet applications in the last decade, the need for
security of information network has increased manifolds. As a primary defense of network …

Anomaly analysis for the classification purpose of intrusion detection system with K-nearest neighbors and deep neural network

K Atefi, H Hashim, M Kassim - 2019 IEEE 7th conference on …, 2019 - ieeexplore.ieee.org
Nowadays, along with network development, due to the threats of unknown sources,
information communication is more vulnerable and require more secured information. An …

M-MultiSVM: An efficient feature selection assisted network intrusion detection system using machine learning

AV Turukmane, R Devendiran - Computers & Security, 2024 - Elsevier
The intrusions are increasing daily, so there is a huge amount of privacy violations, financial
loss, illegal transferring of information, etc. Various forms of intrusion occur in networks, such …

[HTML][HTML] Unleashing the power of Bat optimized CNN-BiLSTM model for advanced network anomaly detection: Enhancing security and performance in IoT …

F Antonius, JC Sekhar, VS Rao, R Pradhan… - Alexandria Engineering …, 2023 - Elsevier
Abstract The growth of IoT (Internet of Things) devices has revolutionized several industries
and brought about novel security threats. Recognizing network anomalies that may point to …

A hybrid anomaly classification with deep learning (DL) and binary algorithms (BA) as optimizer in the intrusion detection system (IDS)

K Atefi, H Hashim, T Khodadadi - 2020 16th IEEE international …, 2020 - ieeexplore.ieee.org
Nowadays, along with network development, due to the threats of unknown sources,
information communication is more vulnerable, and thus, more secured information is …

Anomaly based intrusion detection using filter based feature selection on KDD-CUP 99

P Kushwaha, H Buckchash… - TENCON 2017-2017 IEEE …, 2017 - ieeexplore.ieee.org
DoS, probing, phishing, website defacements etc. are the major problems being faced by the
network users these days. It has led to exposing of the network resources to the attackers …

Implementing scada scenarios and introducing attacks to obtain training data for intrusion detection methods

SD Anton, M Gundall, D Fraunholz… - ICCWS 2019 14th …, 2019 - books.google.com
Cyber-attacks on industrial companies have increased in the last years. The Industrial
Internet of Things increases production efficiency, at the cost of an enlarged attack surface …