Machine learning for anomaly detection: A systematic review
Anomaly detection has been used for decades to identify and extract anomalous
components from data. Many techniques have been used to detect anomalies. One of the …
components from data. Many techniques have been used to detect anomalies. One of the …
Anomaly detection in wireless sensor networks: A survey
M Xie, S Han, B Tian, S Parvin - Journal of Network and computer …, 2011 - Elsevier
Since security threats to WSNs are increasingly being diversified and deliberate, prevention-
based techniques alone can no longer provide WSNs with adequate security. However …
based techniques alone can no longer provide WSNs with adequate security. However …
TSE-IDS: A two-stage classifier ensemble for intelligent anomaly-based intrusion detection system
Intrusion detection systems (IDSs) play a pivotal role in computer security by discovering
and repealing malicious activities in computer networks. Anomaly-based IDS, in particular …
and repealing malicious activities in computer networks. Anomaly-based IDS, in particular …
[HTML][HTML] An ensemble learning framework for anomaly detection in building energy consumption
During building operation, a significant amount of energy is wasted due to equipment and
human-related faults. To reduce waste, today's smart buildings monitor energy usage with …
human-related faults. To reduce waste, today's smart buildings monitor energy usage with …
Anomaly detection using random forest: A performance revisited
R Primartha, BA Tama - 2017 International conference on data …, 2017 - ieeexplore.ieee.org
Intruders have become more and more sophisticated thus a deterrence mechanism such as
an intrusion detection systems (IDS) is pivotal in information security management. An IDS …
an intrusion detection systems (IDS) is pivotal in information security management. An IDS …
[HTML][HTML] A machine learning based intrusion detection system for mobile Internet of Things
Intrusion detection systems plays a pivotal role in detecting malicious activities that
denigrate the performance of the network. Mobile adhoc networks (MANETs) and wireless …
denigrate the performance of the network. Mobile adhoc networks (MANETs) and wireless …
Classifier ensembles: Select real-world applications
Broad classes of statistical classification algorithms have been developed and applied
successfully to a wide range of real-world domains. In general, ensuring that the particular …
successfully to a wide range of real-world domains. In general, ensuring that the particular …
[HTML][HTML] Spatial anomaly detection in sensor networks using neighborhood information
The field of wireless sensor networks (WSNs), embedded systems with sensing and
networking capability, has now matured after a decade-long research effort and …
networking capability, has now matured after a decade-long research effort and …
[HTML][HTML] A procedure for anomaly detection and analysis
Anomaly detection is often used to identify and remove outliers in datasets. However,
detecting and analyzing the pattern of outliers can contribute to future business decisions or …
detecting and analyzing the pattern of outliers can contribute to future business decisions or …
Intrusion detection in mobile ad hoc networks: techniques, systems, and future challenges
Abstract In recent years, Mobile Ad hoc NETworks (MANETs) have generated great interest
among researchers in the development of theoretical and practical concepts, and their …
among researchers in the development of theoretical and practical concepts, and their …