An entropy-based network anomaly detection method
Data mining is an interdisciplinary subfield of computer science involving methods at the
intersection of artificial intelligence, machine learning and statistics. One of the data mining …
intersection of artificial intelligence, machine learning and statistics. One of the data mining …
Detection of network attacks using machine learning and deep learning models
KA Dhanya, S Vajipayajula, K Srinivasan… - Procedia Computer …, 2023 - Elsevier
Anomaly-based network intrusion detection systems are highly significant in detecting
network attacks. Robust machine learning and deep learning models for identifying network …
network attacks. Robust machine learning and deep learning models for identifying network …
NE-GConv: A lightweight node edge graph convolutional network for intrusion detection
Resource constraint devices are now the first choice of cyber criminals for launching
cyberattacks. Network Intrusion Detection Systems (NIDS) play a critical role in the detection …
cyberattacks. Network Intrusion Detection Systems (NIDS) play a critical role in the detection …
Attack detection/prevention system against cyber attack in industrial control systems
Industrial control systems (ICS) are vital for countries' industrial facilities and critical
infrastructures. However, there are not enough security assessments against cyber attacks …
infrastructures. However, there are not enough security assessments against cyber attacks …
A hybrid anomaly classification with deep learning (DL) and binary algorithms (BA) as optimizer in the intrusion detection system (IDS)
Nowadays, along with network development, due to the threats of unknown sources,
information communication is more vulnerable, and thus, more secured information is …
information communication is more vulnerable, and thus, more secured information is …
Variables influencing the effectiveness of signature-based network intrusion detection systems
Contemporary organizations often employ signature-based network intrusion detection
systems to increase the security of their computer networks. The effectiveness of a signature …
systems to increase the security of their computer networks. The effectiveness of a signature …
How does Endpoint Detection use the {MITRE}{ATT&CK} Framework?
MITRE ATT&CK is an open-source taxonomy of adversary tactics, techniques, and
procedures based on real-world observations. Increasingly, organizations leverage ATT&CK …
procedures based on real-world observations. Increasingly, organizations leverage ATT&CK …
Flow-based IDS for ICMPv6-based DDoS attacks detection
Abstract The Internet Control Message Protocol version Six (ICMPv6) is categorized as the
most important part of the Internet Protocol version Six (IPv6) due to its core functionalities …
most important part of the Internet Protocol version Six (IPv6) due to its core functionalities …
SYNTROPY: TCP SYN DDoS attack detection for Software Defined Network based on Rényi entropy
The rapidly evolving landscape of network security, particularly in Software Defined
Networks (SDNs), presents a critical need for efficient and adaptive DDoS attack detection …
Networks (SDNs), presents a critical need for efficient and adaptive DDoS attack detection …
Flow-Based IDS Features Enrichment for ICMPv6-DDoS Attacks Detection
Internet Protocol version 6 (IPv6) and its core protocol, Internet Control Message Protocol
version 6 (ICMPv6), need to be secured from attacks, such as Denial of Service (DoS) and …
version 6 (ICMPv6), need to be secured from attacks, such as Denial of Service (DoS) and …