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EvAnGCN: Evolving Graph Deep Neural Network Based Anomaly Detection in Blockchain.

V. Patel, S. Rajasegarar, L. Pan, J. Liu, and L. Zhu. ADMA (1), volume 13725 of Lecture Notes in Computer Science, page 444-456. Springer, (2022)

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High-dimensional and large-scale anomaly detection using a linear one-class SVM with deep learning.S. Erfani, S. Rajasegarar, S. Karunasekera, and C. Leckie. Pattern Recognit., (2016)Multiclass Anomaly Detector: the CS++ Support Vector Machine.A. Shilton, S. Rajasegarar, and M. Palaniswami. J. Mach. Learn. Res., (2020)A Novel Insider Attack and Machine Learning Based Detection for the Internet of Things.M. Chowdhury, B. Ray, S. Chowdhury, and S. Rajasegarar. ACM Trans. Internet Things, 2 (4): 26:1-26:23 (2021)Visual Structural Assessment and Anomaly Detection for High-Velocity Data Streams.P. Rathore, D. Kumar, J. Bezdek, S. Rajasegarar, and M. Palaniswami. IEEE Trans. Cybern., 51 (12): 5979-5992 (2021)Unsupervised Parameter Estimation for One-Class Support Vector Machines.Z. Ghafoori, S. Rajasegarar, S. Erfani, S. Karunasekera, and C. Leckie. PAKDD (2), volume 9652 of Lecture Notes in Computer Science, page 183-195. Springer, (2016)Smart car parking: Temporal clustering and anomaly detection in urban car parking.Y. Zheng, S. Rajasegarar, C. Leckie, and M. Palaniswami. ISSNIP, page 1-6. IEEE, (2014)Detection of Smoking Events from Confounding Activities of Daily Living.J. Lu, J. Wang, X. Zheng, C. Karmakar, and S. Rajasegarar. ACSW, page 39:1-39:9. ACM, (2019)Multimodal Deep Learning Framework for Sentiment Analysis from Text-Image Web Data.S. Thuseethan, S. Janarthan, S. Rajasegarar, P. Kumari, and J. Yearwood. WI/IAT, page 267-274. IEEE, (2020)Boosting Emotion Recognition in Context using Non-target Subject Information.S. Thuseethan, S. Rajasegarar, and J. Yearwood. IJCNN, page 1-7. IEEE, (2021)Cyber Attack Detection in IoT Networks with Small Samples: Implementation And Analysis.V. Kanthuru, S. Rajasegarar, P. Rathore, R. Doss, L. Pan, B. Ray, M. Chowdhury, C. Srimathi, and M. Durai. ADMA (1), volume 13725 of Lecture Notes in Computer Science, page 118-130. Springer, (2022)

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EvAnGCN: Evolving Graph Deep Neural Network Based Anomaly Detection in Blockchain.

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Disambiguation of "Rajasegarar, Sutharshan"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML EvAnGCN: Evolving Graph Deep Neural Network Based Anomaly Detection in Blockchain.

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EvAnGCN: Evolving Graph Deep Neural Network Based Anomaly Detection in Blockchain.