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1

Yao, Danfeng Daphne, Xiaokui Shu, Long Cheng, and Salvatore J. Stolfo. Anomaly Detection as a Service. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-031-02354-5.

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2

Mehrotra, Kishan G., Chilukuri K. Mohan, and HuaMing Huang. Anomaly Detection Principles and Algorithms. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67526-8.

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3

Wang, Xiaochun. Anomaly Detection in Video Surveillance. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-3023-0.

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4

Wahid, Abdul, and Praveen Kumar Donta. Advanced Techniques for Anomaly Detection. CRC Press, 2025. https://doi.org/10.1201/9781003463559.

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5

Bhuyan, Monowar H., Dhruba K. Bhattacharyya, and Jugal K. Kalita. Network Traffic Anomaly Detection and Prevention. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-65188-0.

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6

Simon, Martin. Anomaly Detection in Random Heterogeneous Media. Springer Fachmedien Wiesbaden, 2015. http://dx.doi.org/10.1007/978-3-658-10993-6.

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7

Peng, Kuan-Chuan, Yizhou Wang, Ziyue Li, et al., eds. Human Activity Recognition and Anomaly Detection. Springer Nature Singapore, 2025. http://dx.doi.org/10.1007/978-981-97-9003-6.

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8

Forrest, R. N. A program to compute magnetic anomaly detection probabilities. Naval Postgraduate School, 1988.

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9

Forrest, R. N. A program to compute magnetic anomaly detection probabilities. 2nd ed. Naval Postgraduate School, 1990.

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10

Alla, Sridhar, and Suman Kalyan Adari. Beginning Anomaly Detection Using Python-Based Deep Learning. Apress, 2019. http://dx.doi.org/10.1007/978-1-4842-5177-5.

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11

Forrest, R. N. A program to compute electric anomaly detection probabilities. Naval Postgraduate School, 1988.

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12

Adari, Suman Kalyan, and Sridhar Alla. Beginning Anomaly Detection Using Python-Based Deep Learning. Apress, 2024. http://dx.doi.org/10.1007/979-8-8688-0008-5.

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13

Burbeck, Kalle. Adaptive real-time anomaly detection for safeguarding critical networks. Department of Computer and Information Science, Linköpings universitet, 2006.

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14

Dinning, Anne. An evaluation of monitoring algorithms for access anomaly detection. Courant Institute of Mathematical Sciences, New York University, 1989.

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15

Dinning, Anne. An evaluation of monitoring algorithms for access anomaly detection. Courant Institute of Mathematical Sciences, New York University, 1989.

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16

Kennedy, Catriona Mairi. Distributed reflective architectures for anomaly detection and autonomous recovery. University of Birmingham, 2003.

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17

Tran, Kim Phuc, ed. Control Charts and Machine Learning for Anomaly Detection in Manufacturing. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-83819-5.

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18

Jin, Shi, Zhaobo Zhang, Krishnendu Chakrabarty, and Xinli Gu. Anomaly-Detection and Health-Analysis Techniques for Core Router Systems. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-33664-6.

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19

Dinning, Anne. An empirical comparison of monitoring algorithms for access anomaly detection. Courant Institute of Mathematical Sciences, New York University, 1989.

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20

Dinning, Anne. An empirical comparison of monitoring algorithms for access anomaly detection. Courant Institute of Mathematical Sciences, New York University, 1989.

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21

Isupova, Olga. Machine Learning Methods for Behaviour Analysis and Anomaly Detection in Video. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-75508-3.

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22

Kaya, Mehmet, Sleiman Alhajj, Kashfia Sailunaz, and Min-Yuh Day, eds. Social Network Analysis and Mining Applications in Healthcare and Anomaly Detection. Springer Nature Switzerland, 2024. https://doi.org/10.1007/978-3-031-75204-9.

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23

Jakimovski, Bojan. Biologically Inspired Approaches for Locomotion, Anomaly Detection and Reconfiguration for Walking Robots. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22505-5.

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24

Beigi, Mandis. On Optimal Quantization and its Effect on Anomaly Detection and Image Classification. [publisher not identified], 2013.

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25

service), SpringerLink (Online, ed. Biologically Inspired Approaches for Locomotion, Anomaly Detection and Reconfiguration for Walking Robots. Springer-Verlag GmbH Berlin Heidelberg, 2011.

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26

Kahn, Alan. Applying Anomaly Detection to Search for New Physics with the ATLAS Detector at the Large Hadron Collider. [publisher not identified], 2022.

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27

Usman, Muhammad, Vallipuram Muthukkumarasamy, Xin-Wen Wu, and Surraya Khanum. Mobile Agent-Based Anomaly Detection and Verification System for Smart Home Sensor Networks. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7467-7.

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28

United States. National Aeronautics and Space Administration., ed. System for anomaly and failure detection system development: Final report 30 September 1993. Rockwell International, Rocketdyne Division, 1993.

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29

United States. National Aeronautics and Space Administration., ed. System for Anomaly and Failure Detection system development: Final report 24 July 1992. Rockwell International, Rocketdyne Division, 1992.

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30

United States. National Aeronautics and Space Administration., ed. System for Anomaly and Failure Detection system development: Final report 24 July 1992. Rockwell International, Rocketdyne Division, 1992.

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31

Baus, Wolfgang W. Magnetic anomaly detection using conventional and superconductive sensors with respect to vehicle monitoring. Brockmeyer, 1995.

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32

Cuadra-Sánchez, Antonio, and Javier Aracil-Rico. Traffic Anomaly Detection. Elsevier, 2015.

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33

Traffic Anomaly Detection. Elsevier, 2015. http://dx.doi.org/10.1016/c2015-0-01239-4.

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34

Cuadra-Sánchez, Antonio, and Javier Aracil-Rico. Traffic Anomaly Detection. ISTE Press Limited - Elsevier Incorporated, 2015.

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35

Mehrotra, Kishan G., Chilukuri K. Mohan, and HuaMing Huang. Anomaly Detection Principles and Algorithms. Springer, 2019.

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36

Anomaly Detection in Video Surveillance. Springer, 2024.

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37

Banu, Saira. Anomaly Detection: Techniques and Applications. Nova Science Publishers, Incorporated, 2021.

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38

Mehrotra, Kishan G., Chilukuri K. Mohan, and HuaMing Huang. Anomaly Detection Principles and Algorithms. Springer, 2018.

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39

Banu, Saira. Anomaly Detection: Techniques and Applications. Nova Science Publishers, Incorporated, 2021.

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40

Handbook of Anomaly Detection : with Python Outlier Detection: Build and Modernize Your Anomaly Detection Models with Examples. Independently Published, 2023.

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41

Beginning Anomaly Detection Using Python-Based Deep Learning: Implement Anomaly Detection Applications with Keras and Pytorch. Apress L. P., 2023.

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42

Bhattacharyya, Dhruba Kumar, and Jugal Kumar Kalita. Network Anomaly Detection: A Machine Learning Perspective. Taylor & Francis Group, 2013.

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43

Bhattacharyya, Dhruba Kumar. Network Anomaly Detection: A Machine Learning Perspective. Taylor & Francis Group, 2013.

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44

Bhattacharyya, Dhruba Kumar, and Jugal Kumar Kalita. Network Anomaly Detection: A Machine Learning Perspective. Taylor & Francis Group, 2013.

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45

Network anomaly detection: A machine learning perspective. CRC Press, Taylor & Francis Group, 2014.

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46

Simon, Cher. Deep Learning and XAI Techniques for Anomaly Detection: Integrating Theory and Practice of Explainable Deep Learning Anomaly Detection. Packt Publishing, Limited, 2023.

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47

Khatri, Dr Rajkumar. Anomaly detection approach for detecting anomalies using netflow records and spark. Createspace Independent Publishing Platform, 2017.

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48

Roopaei, Mehdi, and Peyman Najafirad (Paul Rad). Applied Cloud Deep Semantic Recognition: Advanced Anomaly Detection. Auerbach Publishers, Incorporated, 2018.

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49

Roopaei, Mehdi, and Peyman Najafirad (Paul Rad). Applied Cloud Deep Semantic Recognition: Advanced Anomaly Detection. Auerbach Publishers, Incorporated, 2018.

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50

Roopaei, Mehdi, and Peyman Najafirad (Paul Rad). Applied Cloud Deep Semantic Recognition: Advanced Anomaly Detection. Auerbach Publishers, Incorporated, 2018.

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