Publications

S. Shao, S. Alharir, P. Satam, S. Shiri, and A. Mbarki, "AI-based Arabic Language and Speech Tutor," the 19th IEEE/ACS International Conference on Computer Systems and Applications. 2022 (accepted for publication).
M. Rahman, S. Shao, P. Satam, S. Hariri, C. Padilla, Z. Taylor, C. Nevarez, "A BERT-based Deep Learning Approach for Reputation Analysis in Social Media", the 19th IEEE/ACS International Conference on Computer Systems and Applications 2022 (accepted for publication).
M.M. Abrar, R. Islam, P. Satam, S. Satam, S. Shao and S. Hariri, “Intrusion Detection in Global Positioning System (GPS: Threat Detection Framework and a Public Dataset,” IEEE Access, submitted August 2022 (under review).

Liu, H (2021), “Algorithms for Scalability and Security in Adversarial Environments,” PhD Thesis, University of Arizona, March 2021.
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.
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.
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.
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.
Satam, S., Satam, P., Pacheco, & Hariri, S. (2021, Accepted). Security Framework for Smart Cyber Infrastructure. Cluster Computing, vol. 25, no. x.
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.
N. Teku, T. Bose, “Cognitive Diversity Equalization for 2x2 HF MIMO Channels,” International Telemetry Conference, 2021.
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.
A. Torres, P. Satam, T. Bose, “Machine Learning Classifiers for Anomaly Based Wireless Intrusion Detection,” International Telemetry Conference, 2021.
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.
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.
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).
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.
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.
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.
D. Schwartz, G. Ditzler (2021) “Bolstering Adversarial Robustness with Latent Disparity Regularization,” IEEE/INNS International Joint Conference on Neural Networks.
S Hess, G Ditzler (2021) “OrderNet: Sorting High Dimensional Low Sample Data with Few-Shot Learning,” IEEE/INNS International Joint Conference on Neural Networks.
H. Liu and G. Ditzler (2021) “Data Poisoning Against Information-Theoretic Feature Selection,” Information Sciences, vol. 573, pp. 396-411.

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).
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.
H. Liu and G. Ditzler, “Poisoning mRMR with Adversarial Data,” IEEE International Conference on Acoustics, Speech and Signal Processing, 2019
Liu, D. Schwartz (2020) Building Data Science Pipelines for Intrusion Detection.
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
H. Liu and G. Ditzler, “Bypassing Temporal Dependency in Adversarial Audio Examples,” IEEE Symposium Series on Computational Intelligence, 2020.
Szep, Jeno, and Salim Hariri. "Paralinguistic Classification of Mask Wearing by Image Classifiers and Fusion." Proceedings INTERSPEECH. Shanghai, China: ISCA (2020): 2087-2091.
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.
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
Liu, (2020) Adversarial Machine Learning for Audio Analysis, University of Arizona.
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.
Liu and G. Ditzler (2020) “Bypassing Temporal Dependency in Adversarial Audio Examples,” IEEE Symposium Series on Computational Intelligence.
H. Liu and G. Ditzler, “Detecting Adversarial Audio via Activation Quantization Error,” IEEE/INNS International Joint Conference on Neural Networks, 2020
M.Elkadi, T. Bose, (2020) “A Suite of Equalizers and Cognitive Engines for GNU Radio,” International Telemetering Conference (ITC).
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.
Berian, A., Staab, K., Teku, N., Ditzler, G., Bose, T., & Tandon, R. (2020). Adversarial Filters for Secure Modulation Classification. arXiv preprint arXiv:2008.06785.
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.
Liu and G. Ditzler, (2020) “Data Poisoning Against Information-Theoretic Feature Selection” submitted to Information Sciences.
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.
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.
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.
T. Peken, T., Tandon, R., & Bose, T. (2019). Reinforcement Learning for Hybrid Beamforming In Millimeter Wave Systems. International Foundation for Telemetering.
M.Elkadi, T. Bose, (2020) "A Suite of Equalizers and Cognitive Engines for GNU Radio," International Telemetering Conference (ITC).
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.
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.
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).

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.
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.
H. Liu and G. Ditzler, (2019) “A Semi-Parallel Framework for Greedy Information-Theoretic Feature Selection,” Information Sciences, vol. 492, pp. 13-28.
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.
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.

2022

S. Shao, S. Alharir, P. Satam, S. Shiri, and A. Mbarki, "AI-based Arabic Language and Speech Tutor," the 19th IEEE/ACS International Conference on Computer Systems and Applications. 2022 (accepted for publication).

M. Rahman, S. Shao, P. Satam, S. Hariri, C. Padilla, Z. Taylor, C. Nevarez, "A BERT-based Deep Learning Approach for Reputation Analysis in Social Media", the 19th IEEE/ACS International Conference on Computer Systems and Applications 2022 (accepted for publication).

M.M. Abrar, R. Islam, P. Satam, S. Satam, S. Shao and S. Hariri, “Intrusion Detection in Global Positioning System (GPS: Threat Detection Framework and a Public Dataset,” IEEE Access, submitted August 2022 (under review).

2021

Liu, H (2021), “Algorithms for Scalability and Security in Adversarial Environments,” PhD Thesis, University of Arizona, March 2021.

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.

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.

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.

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.

Satam, S., Satam, P., Pacheco, & Hariri, S. (2021, Accepted). Security Framework for Smart Cyber Infrastructure. Cluster Computing, vol. 25, no. x.

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.

N. Teku, T. Bose, “Cognitive Diversity Equalization for 2x2 HF MIMO Channels,” International Telemetry Conference, 2021.

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.

A. Torres, P. Satam, T. Bose, “Machine Learning Classifiers for Anomaly Based Wireless Intrusion Detection,” International Telemetry Conference, 2021.

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.

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.

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).

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.

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.

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.

D. Schwartz, G. Ditzler (2021) “Bolstering Adversarial Robustness with Latent Disparity Regularization,” IEEE/INNS International Joint Conference on Neural Networks.

S Hess, G Ditzler (2021) “OrderNet: Sorting High Dimensional Low Sample Data with Few-Shot Learning,” IEEE/INNS International Joint Conference on Neural Networks.

H. Liu and G. Ditzler (2021) “Data Poisoning Against Information-Theoretic Feature Selection,” Information Sciences, vol. 573, pp. 396-411.

2020

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).

H. Liu and G. Ditzler, “Poisoning mRMR with Adversarial Data,” IEEE International Conference on Acoustics, Speech and Signal Processing, 2019

Liu, D. Schwartz (2020) Building Data Science Pipelines for Intrusion Detection.

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

H. Liu and G. Ditzler, “Bypassing Temporal Dependency in Adversarial Audio Examples,” IEEE Symposium Series on Computational Intelligence, 2020.

Szep, Jeno, and Salim Hariri. "Paralinguistic Classification of Mask Wearing by Image Classifiers and Fusion." Proceedings INTERSPEECH. Shanghai, China: ISCA (2020): 2087-2091.

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.

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

Liu, (2020) Adversarial Machine Learning for Audio Analysis, University of Arizona.

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.

Liu and G. Ditzler (2020) “Bypassing Temporal Dependency in Adversarial Audio Examples,” IEEE Symposium Series on Computational Intelligence.

H. Liu and G. Ditzler, “Detecting Adversarial Audio via Activation Quantization Error,” IEEE/INNS International Joint Conference on Neural Networks, 2020

M.Elkadi, T. Bose, (2020) “A Suite of Equalizers and Cognitive Engines for GNU Radio,” International Telemetering Conference (ITC).

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.

Berian, A., Staab, K., Teku, N., Ditzler, G., Bose, T., & Tandon, R. (2020). Adversarial Filters for Secure Modulation Classification. arXiv preprint arXiv:2008.06785.

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.

Liu and G. Ditzler, (2020) “Data Poisoning Against Information-Theoretic Feature Selection” submitted to Information Sciences.

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.

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.

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.

T. Peken, T., Tandon, R., & Bose, T. (2019). Reinforcement Learning for Hybrid Beamforming In Millimeter Wave Systems. International Foundation for Telemetering.

M.Elkadi, T. Bose, (2020) "A Suite of Equalizers and Cognitive Engines for GNU Radio," International Telemetering Conference (ITC).

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.

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.

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).

2019

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.

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.

H. Liu and G. Ditzler, (2019) “A Semi-Parallel Framework for Greedy Information-Theoretic Feature Selection,” Information Sciences, vol. 492, pp. 13-28.

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.

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.