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Liu, H (2021), “Algorithms for Scalability and Security in Adversarial Environments,” PhD Thesis, University of Arizona, March 2021.
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Aashma Uprety and Danda B. Rawat, "Reinforcement Learning for IoT Security: A Comprehensive Survey," IEEE Internet of Things Journal, Vol. 8, No. 11, pp. : 8693 - 8706, June 2021.
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Ronald Doku and Danda B. Rawat, "Mitigating Data Poisoning Attacks on a Federated LearningEdge Computing Network," Proc. of the IEEE Consumer Communications & Networking Conference (IEEE CCNC 2021), 9-12 January 2021, Las Vegas, NV, USA, Virtual Conference.
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Wu, C., Shao, S., Tunc, C., Satam, P., & Hariri, S. (2021, Accepted). An explainable and efficient deep learning framework for video anomaly detection. Cluster Computing, vol. 25, no. x.
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Abdulhamid Adebayo and Danda B. Rawat, "Cyber Deception for Wireless Network Virtualization using Stackelberg Game Theory," Proc. of the IEEE Consumer Communications & Networking Conference (IEEE CCNC 2021), 9-12 January 2021, Las Vegas, NV, USA, Virtual Conference.
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Satam, S., Satam, P., Pacheco, & Hariri, S. (2021, Accepted). Security Framework for Smart Cyber Infrastructure. Cluster Computing, vol. 25, no. x.
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S. Shao, P. Satam, S. Satam, G. Ditzler, S. Hariri, C. Tunc (2021) “Multi-Layer Mapping of Cyberspace for Intrusion Detection,” (2021, Accepted). ACS/IEEE International Conference on Computer Systems and Applications.
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N. Teku, T. Bose, “Cognitive Diversity Equalization for 2x2 HF MIMO Channels,” International Telemetry Conference, 2021.
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K. Anand, C. Goodluck, N. Teku, Q. Nguyen, T. Bose, R. Thamvichai, “Pairing a Cognitive Engine with a Neural Network Modulation Classifier,” International Telemetry Conference, 2021.
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A. Torres, P. Satam, T. Bose, “Machine Learning Classifiers for Anomaly Based Wireless Intrusion Detection,” International Telemetry Conference, 2021.
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M.R. Tanniru, N. Agarwal, A. Sokan, and S. Hariri, “An Agile Digital Platform to Support Population Health—A Case Study of a Digital Platform to Support Patients with Delirium Using IoT, NLP, and AI,” International journal of environmental research and public health,18, no. 11 (2021): 5686.
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C. Wu, J. Szep, S. Hariri, N.K. Agarwal, S.K. Agarwal, and C., “SeVA: An AI Solution for Age Friendly Care of Hospitalized Older Adults.” HEALTHINF, pp. 583-591, 2021.
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B. Ghimire and D.B. Rawat, “Secure, Privacy Preserving and Verifiable Federating Learning using Blockchain for Internet of Vehicles,” IEEE Consumer Electronics Magazine, June 2021 (accepted for publication).
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E. Muhati and D.B. Rawat, “ASAP: Anti-Spoofing Aphorism using Path-analysis,” Proc. of the IEEE/ACM International Symposium on Quality of Service (IEEE/ACM IWQoS 2021), 25-28 June 2021.
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A. Uprety and D.B. Rawat, “Reinforcement Learning for IoT Security: A Comprehensive, Survey,” IEEE Internet of Things Journal, vol. 8, no. 11, pp. 8693 - 8706, June 2021.
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Aashma Uprety, Danda B. Rawat and Jiang Li, "Privacy Preserving Misbehavior Detection in IoV using Federated Machine Learning," Proc. of the IEEE Consumer Communications & Networking Conference (IEEE CCNC 2021), 9-12 January 2021, Las Vegas, NV, USA, Virtual Conference.
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D. Schwartz, G. Ditzler (2021) “Bolstering Adversarial Robustness with Latent Disparity Regularization,” IEEE/INNS International Joint Conference on Neural Networks.
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S Hess, G Ditzler (2021) “OrderNet: Sorting High Dimensional Low Sample Data with Few-Shot Learning,” IEEE/INNS International Joint Conference on Neural Networks.
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H. Liu and G. Ditzler (2021) “Data Poisoning Against Information-Theoretic Feature Selection,” Information Sciences, vol. 573, pp. 396-411.
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Satam, Pratik, and Salim Hariri. "WIDS: An Anomaly Based Intrusion Detection System for Wi-Fi (IEEE 802.11) Protocol." IEEE Transactions on Network and Service Management (2020).
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F. Olowononi, D.B. Rawat, and C. Liu, "Trust-Based Adversarial Resiliency in Vehicular Cyber Physical Systems Using Reinforcement Learning" Proc. of the Eighth International Symposium on Security in Computing and Communications (SSCC'20) - SSCC’20, Special Session, Chennai, India, October 14-17, 2020.
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H. Liu and G. Ditzler, “Poisoning mRMR with Adversarial Data,” IEEE International Conference on Acoustics, Speech and Signal Processing, 2019
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Liu, D. Schwartz (2020) Building Data Science Pipelines for Intrusion Detection.
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Spillane, S., Jung, K. H., Bowers, K., Peken, T., Marefat, M. H., & Bose, T. (2020, July). Machine Learning Based MIMO Equalizer for High Frequency (HF) Communications. In 2020 International Joint Conference on Neural Networks (IJCNN) (pp. 1-8). IEEE
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H. Liu and G. Ditzler, “Bypassing Temporal Dependency in Adversarial Audio Examples,” IEEE Symposium Series on Computational Intelligence, 2020.
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Szep, Jeno, and Salim Hariri. "Paralinguistic Classification of Mask Wearing by Image Classifiers and Fusion." Proceedings INTERSPEECH. Shanghai, China: ISCA (2020): 2087-2091.
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Satam, Shalaka, Pratik Satam, and Salim Hariri. "Multi-level Bluetooth Intrusion Detection System." In 2020 IEEE/ACS 17th International Conference on Computer Systems and Applications (AICCSA), pp. 1-8. IEEE, 2020.
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Yao, Likai, Cihan Tunc, Pratik Satam, and Salim Hariri. "Resilient Machine Learning (rML) Ensemble Against Adversarial Machine Learning Attacks." In International Conference on Dynamic Data Driven Application Systems, pp. 274-282. Springer, Cham, 2020
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Liu, (2020) Adversarial Machine Learning for Audio Analysis, University of Arizona.
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Wu, Chongke, Sicong Shao, Cihan Tunc, and Salim Hariri. "Video anomaly detection using pretrained deep convolutional neural nets and context mining." In 2020 IEEE/ACS 17th International Conference on Computer Systems and Applications (AICCSA), pp. 1-8. IEEE, 2020.
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Liu and G. Ditzler (2020) “Bypassing Temporal Dependency in Adversarial Audio Examples,” IEEE Symposium Series on Computational Intelligence.
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H. Liu and G. Ditzler, “Detecting Adversarial Audio via Activation Quantization Error,” IEEE/INNS International Joint Conference on Neural Networks, 2020
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M.Elkadi, T. Bose, (2020) “A Suite of Equalizers and Cognitive Engines for GNU Radio,” International Telemetering Conference (ITC).
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K.-S. Peng, G. Ditzler, and J. Rozenblit (2020) “A Light-Weight Monocular Depth Estimation with Edge-Guided Occlusion Fading Reduction,” International Symposium on Visual Computing.
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Berian, A., Staab, K., Teku, N., Ditzler, G., Bose, T., & Tandon, R. (2020). Adversarial Filters for Secure Modulation Classification. arXiv preprint arXiv:2008.06785.
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K.-S. Peng, G. Ditzler, and J. Rozenblit (2020) “Self-Supervised Correlational Monocular Depth Estimation using a Hybrid Network,” submitted IEEE Transactions on Neural Networks and Learning Systems.
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Liu and G. Ditzler, (2020) “Data Poisoning Against Information-Theoretic Feature Selection” submitted to Information Sciences.
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Spillane, S., Jung, K. H., Bowers, K., Peken, T., Marefat, M. H., & Bose, T. (2020, July). Machine Learning Based MIMO Equalizer for High Frequency (HF) Communications. In 2020 International Joint Conference on Neural Networks (IJCNN) (pp. 1-8). IEEE.
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Peken, T., Adiga, S., Tandon, R., & Bose, T. (2020). Deep Learning for SVD and Hybrid Beamforming. IEEE Transactions on Wireless Communications, 19(10), 6621-6642.
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T. Peken, R. Tandon, and T. Bose, "Unsupervised mmWave Beamforming via Autoencoders," Proc. of the IEEE International Conference on Communications (ICC), pp. 1-6, June 2020.
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T. Peken, T., Tandon, R., & Bose, T. (2019). Reinforcement Learning for Hybrid Beamforming In Millimeter Wave Systems. International Foundation for Telemetering.
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M.Elkadi, T. Bose, (2020) "A Suite of Equalizers and Cognitive Engines for GNU Radio," International Telemetering Conference (ITC).
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P. K. Singh, A. Agarwal, G. Nakum, D. B. Rawat and S. Nandi, "MPFSLP: Masqueraded Probabilistic Flooding for Source-Location Privacy in VANETs," IEEE Transactions on Vehicular Technology, Vol. 69, No. 10, pp. 11383 - 11393, October 2020.
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A. Berian, I. Aykin, M. Krunz and T. Bose, "Deep Learning Based Identification of Wireless Protocols in the PHY layer," International Conference on Computing, Networking and Communications (ICNC), Big Island, HI, USA, 2020, pp. 287-293, doi: 10.1109/ICNC47757.2020.9049732.
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Shao, Sicong, Cihan Tunc, Amany Al-Shawi, and Salim Hariri, (2020) “Ensemble of Ensemble Learning-based Author Attribution for Internet Relay Chat Forensics,” ACM Transactions on Management Information Systems (TMIS).
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K.S. Peng, G. Ditzler, and J. Rozenblit, (2019) “Self-Supervised Correlatonal Monocular Depth Estimation using ResVGG Network,” International Conference on Intelligent Systems and Image Processing.
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G. Ditzler, S. Miller, and J. Rozenblit, (2019) “Learning What We Don’t Care About: Regularization with Sacrificial Functions,” Information Sciences, vol. 496, pp. 198-211.
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H. Liu and G. Ditzler, (2019) “A Semi-Parallel Framework for Greedy Information-Theoretic Feature Selection,” Information Sciences, vol. 492, pp. 13-28.
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Shao, Sicong, Cihan Tunc, Amany Al-Shawi, and Salim Hariri, (2019) “One-Class Classification with Deep Autoencoder Neural Networks for Author Verification in Internet Relay Chat.” In 2019 IEEE/ACS 16th International Conference on Computer Systems and Applications (AICCSA), pp. 1-8. IEEE.
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Shao, Sicong, Cihan Tunc, Amany Al-Shawi, and Salim Hariri, (2019) “Automated Twiter Author Clustering with Unsupervised Learning for Social Media Forensics.” In 2019 IEEE/ACS 16th International Conference on Computer Systems and Applications (AICCSA), pp. 1-8. IEEE.