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A Survey of AI-Based Anomaly Detection in IoT and Sensor Networks
Sensors, 2023 Machine learning (ML) and deep learning (DL), in particular, are common tools for anomaly detection (AD). With the rapid increase in the number of Internet-connected devices, the growing desire for Internet of Things (IoT) devices in the home, on our ...
Kyle DeMedeiros +2 more
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Dendritic Cells for Anomaly Detection [PDF]
SSRN Electronic Journal, 2006 Artificial immune systems, more specifically the negative selection algorithm, have previously been applied to intrusion detection. The aim of this research is to develop an intrusion detection system based on a novel concept in immunology, the Danger Theory.
Greensmith, Julie +2 more
openaire +5 more sources
发电技术, 2021 Anomaly detection of gas turbine hot components can ensure its operational safety and reliability. With the boom of artificial intelligence, data-driven fault diagnosis is becoming increasingly popular.
Mingliang BAI +4 more
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E-SFD: Explainable Sensor Fault Detection in the ICS Anomaly Detection System
IEEE Access, 2021 Industrial Control Systems (ICS) are evolving into smart environments with increased interconnectivity by being connected to the Internet. These changes increase the likelihood of security vulnerabilities and accidents. As the risk of cyberattacks on ICS
Chanwoong Hwang, Taejin Lee
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Anomaly Detection in Manufacturing
, 2023 AbstractThis chapter provides an introduction to common methods of anomaly detection, which is an important aspect of quality control in manufacturing. We give an overview of widely used statistical methods for detecting anomalies based on k-means, decision trees, and Support Vector Machines.
Scholz, Jona +3 more
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An Immune Inspired Approach to Anomaly Detection [PDF]
, 2007 The immune system provides a rich metaphor for computer security: anomaly detection that works in nature should work for machines. However, early artificial immune system approaches for computer security had only limited success.
Aickelin, Uwe, Twycross, Jamie
core +4 more sources
Network Anomaly Detection by Using a Time-Decay Closed Frequent Pattern
Information, 2019 Anomaly detection of network traffic flows is a non-trivial problem in the field of network security due to the complexity of network traffic. However, most machine learning-based detection methods focus on network anomaly detection but ignore the user ...
Ying Zhao +6 more
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Anomaly Detection with Partially Observed Anomalies [PDF]
Companion of the The Web Conference 2018 on The Web Conference 2018 - WWW '18, 2018 In this paper, we consider the problem of anomaly detection. Previous studies mostly deal with this task in either supervised or unsupervised manner according to whether label information is available. However, there always exists settings which are different from the two standard manners.
Jun Zhou +4 more
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A steam turbine anomaly detection method based on O-DAE and SVDD
Zhejiang dianli, 2023 Anomaly detection in unlabeled and highly imbalanced monitoring data is one of the most urgent to be solved and challenging industry problems. The use of autoencoders for anomaly detection is becoming more and more popular due to the powerful high ...
XU Weimin +5 more
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Conflict-driven Hybrid Observer-based Anomaly Detection
, 2017 This paper presents an anomaly detection method using a hybrid observer -- which consists of a discrete state observer and a continuous state observer. We focus our attention on anomalies caused by intelligent attacks, which may bypass existing anomaly ...
balluchi +10 more
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