A survey of distance and similarity measures used within network intrusion anomaly detection
DJ Weller-Fahy, BJ Borghetti… - … Surveys & Tutorials, 2014 - ieeexplore.ieee.org
Anomaly detection (AD) use within the network intrusion detection field of research, or
network intrusion AD (NIAD), is dependent on the proper use of similarity and distance …
network intrusion AD (NIAD), is dependent on the proper use of similarity and distance …
A survey of intrusion detection in wireless network applications
R Mitchell, R Chen - Computer Communications, 2014 - Elsevier
Abstract Information systems are becoming more integrated into our lives. As this integration
deepens, the importance of securing these systems increases. Because of lower installation …
deepens, the importance of securing these systems increases. Because of lower installation …
[图书][B] The state of the art in intrusion prevention and detection
ASK Pathan - 2014 - api.taylorfrancis.com
Most of the security threats in various communications networks are posed by the illegitimate
entities that enter or intrude within the network perimeter, which could commonly be termed …
entities that enter or intrude within the network perimeter, which could commonly be termed …
Machine learning techniques for intrusion detection
M Zamani, M Movahedi - arXiv preprint arXiv:1312.2177, 2013 - arxiv.org
An Intrusion Detection System (IDS) is a software that monitors a single or a network of
computers for malicious activities (attacks) that are aimed at stealing or censoring …
computers for malicious activities (attacks) that are aimed at stealing or censoring …
Machine learning for traffic analysis: a review
Traffic analysis has many purposes such as evaluating the performance and security of
network operations and management. Therefore, network traffic analysis is considered vital …
network operations and management. Therefore, network traffic analysis is considered vital …
Feature selection and dynamic network traffic congestion classification based on machine learning for Internet of Things
A Elngar, A Burlea-Schiopoiu - Wasit Journal of Computer and …, 2023 - wjcm.uowasit.edu.iq
The network traffic congestion classifier is essential for network monitoring systems. Network
traffic characterization is a methodology to classify traffic into several classes supporting …
traffic characterization is a methodology to classify traffic into several classes supporting …
Intrusion detection system for wireless sensor networks using danger theory immune-inspired techniques
HM Salmon, CM De Farias, P Loureiro… - International journal of …, 2013 - Springer
An IDS framework inspired in the Human Immune System to be applied in the wireless
sensor network context is proposed. It uses an improved decentralized and customized …
sensor network context is proposed. It uses an improved decentralized and customized …
Denial of service attack detection using dendritic cell algorithm
Denial-of-service (DoS) and distributed denial-of-service (DDoS) is one of the most popular
and easy-to-implement attacks targeting online systems and networks. This paper presents …
and easy-to-implement attacks targeting online systems and networks. This paper presents …
An adaptive early node compromise detection scheme for hierarchical WSNs
A Al-Riyami, N Zhang, J Keane - IEEE Access, 2016 - ieeexplore.ieee.org
Node compromise attacks pose a serious threat to wireless sensor networks (WSNs). To
launch an attack, an adversary physically captures a node and access data or software …
launch an attack, an adversary physically captures a node and access data or software …
[PDF][PDF] Network Topology Classification in SDN Ecosystem using Machine Learning
J Yadav, KP Ahire - Int. J. Next-Gener. Comput, 2022 - researchgate.net
To meet the increasing network demands of enterprise environments and data centers,
traditional network architectures have been replaced by software-enabled hardware devices …
traditional network architectures have been replaced by software-enabled hardware devices …