Hyperspectral Anomaly Detection with Auto-Encoder and Independent Target by Shuhan Chen, Xiaorun Li, Yunfeng Yan

“…Many AE-based background (BKG) modeling methods have been developed for hyperspectral anomaly detection (HAD). However, their performance is subject to their unbiased reconstruction of BKG and target pixels. …”
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Entropy-Based Anomaly Detection for Gaussian Mixture Modeling by Luca Scrucca

“…This latter aspect is crucial for anomaly detection in situations where a clear, early warning of an abnormal condition is required. …”
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Clustering based background learning for hyperspectral anomaly detection by Mohamad Ebrahim Aghili, Maryam Imani, Hassan Ghassemian

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Anomaly Detection for IOT Systems Using Active Learning by Mohammed Zakariah, Abdulaziz S. Almazyad

Subjects: “…anomaly detection…”
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Anomaly Detection Method of SDN Network Edge Switch by ZHAO Yang, YI Peng, ZHANG Zhen, HU Tao, LIU Shaoxun

“…Software-defined network gives programmability to the network,reduces the complexity of network management,and promotes the development of new network technology.As a device for data forwarding and policy enforcement,the permissions of SDN switches should not be stolen by unauthorized entities.However,the SDN switch does not always execute the commands issued by the controller.Malicious attackers attack the network covertly and fatally by eroding the SDN switch,which seriously affects the end-to-end communication quality of users.Communicationsequential process(CSP),as a modeling language designed for concurrent systems,can accurately describe the interaction between SDN switch-switch and switch-host.In this paper,CSP is used to model SDN switch and terminal host,and two abnormal switch location methods are analyzed theoretically.We verify the effectiveness of the two detection methods in the instantiated model system when the edge switch is maliciously forwarded as an egress switch,and the authentication results show that the abnormal behavior cannot be detected.In order to solve this problem,an anomaly detection method for edge switch is proposed in this paper.In this method,the host records the statistical information and triggers the packet_in message to complete the information transmission with the controller by constructing a special packet.The controller collects the statistical information and detects the abnormal forwarding behavior of the edge switch by analyzing the statistical information consistency between the edge switch and the host.Finally,based on the ryu controller,experiments are carried out on the mininet platform,and experimental results show that the edge switch anomaly detection method can successfully detect abnormal behavior.…”
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Contrastive-Regularized U-Net for Video Anomaly Detection by Kian Yu Gan, Yu Tong Cheng, Hung-Khoon Tan, Hui-Fuang Ng, Maylor Karhang Leung, Joon Huang Chuah

Subjects: “…video anomaly detection…”
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Network anomaly detection using deep learning techniques by Mohammad Kazim Hooshmand, Doreswamy Hosahalli

“…To transform this performance towards the task of network anomaly detection in cyber‐security, this study proposes a model using one‐dimensional CNN architecture. …”
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Exploring the Intrinsic Probability Distribution for Hyperspectral Anomaly Detection by Shaoqi Yu, Xiaorun Li, Shuhan Chen, Liaoying Zhao

Subjects: “…hyperspectral anomaly detection…”
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Comparing Autoencoder and Isolation Forest in Network Anomaly Detection by Timotej Smolen, Lenka Benova

Subjects: “…anomaly detection network traffic intrusion detection autoencoder isolation forest lstm unsupervised learning web server logs…”
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Anomaly Detection Based on Convex Analysis: A Survey by Tong Wang, Mengsi Cai, Mengsi Cai, Xiao Ouyang, Ziqiang Cao, Tie Cai, Xu Tan, Xin Lu, Xin Lu

Subjects: “…anomaly detection…”
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Weighted Sparseness-Based Anomaly Detection for Hyperspectral Imagery by Xing Lian, Erwei Zhao, Wei Zheng, Xiaodong Peng, Ang Li, Zheng Zhen, Yan Wen

Subjects: “…anomaly detection…”
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Unsupervised Transformer-Based Anomaly Detection in ECG Signals by Abrar Alamr, Abdelmonim Artoli

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Perfect Density Models Cannot Guarantee Anomaly Detection by Charline Le Lan, Laurent Dinh

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Real‐time video anomaly detection for smart surveillance by Manal Mostafa Ali

Subjects: “…anomaly detection…”
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Network anomaly detection using artificial neural networks by Sergey Andropov, Alexei Guirik, Mikhail Budko, Marina Budko

Subjects: “…anomaly detection…”
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Anomaly Detection in Multi-Seasonal Time Series Data by Ashton T. Williams, Ryan E. Sperl, Soon M. Chung

Subjects: “…Anomaly detection…”
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CBAM: A Contextual Model for Network Anomaly Detection by Henry Clausen, Gudmund Grov, David Aspinall

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Trust-Based Anomaly Detection in Emerging Sensor Networks by Renyong Wu, Xue Deng, Rongxing Lu, Xuemin (Sherman) Shen

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Entropy-Based Anomaly Detection in Household Electricity Consumption by Marta Moure-Garrido, Celeste Campo, Carlos Garcia-Rubio

Subjects: “…anomaly detection…”
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Subfeature Ensemble-Based Hyperspectral Anomaly Detection Algorithm by Shuo Wang, Wei Feng, Yinghui Quan, Wenxing Bao, Gabriel Dauphin, Lianru Gao, Xian Zhong, Mengdao Xing

Subjects: “…Anomaly detection…”
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