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2SMaRT: A Two-Stage Machine Learning-Based Approach for Run-Time Specialized Hardware-Assisted Malware Detection.

H. Sayadi, H. Makrani, S. Dinakarrao, T. Mohsenin, A. Sasan, S. Rafatirad, and H. Homayoun. DATE, page 728-733. IEEE, (2019)

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Contextual Augmentation of Ontology for Recognizing Sub-events.S. Rafatirad, and R. Jain. ICSC, page 546-553. IEEE Computer Society, (2011)Programmable Gates Using Hybrid CMOS-STT Design to Prevent IC Reverse Engineering.T. Winograd, G. Shenoy, H. Salmani, H. Mahmoodi, S. Rafatirad, and H. Homayoun. ACM Trans. Design Autom. Electr. Syst., 23 (6): 76:1-76:21 (2018)Mitigating the Performance and Quality of Parallelized Compressive Sensing Reconstruction Using Image Stitching.M. Namazi, H. Makrani, Z. Tian, S. Rafatirad, M. Akbari, A. Sasan, and H. Homayoun. ACM Great Lakes Symposium on VLSI, page 219-224. ACM, (2019)A comprehensive study of visual event computing.W. Yan, D. Kieran, S. Rafatirad, and R. Jain. Multimedia Tools Appl., 55 (3): 443-481 (2011)Estimating the Circuit Deobfuscating Runtime based on Graph Deep Learning.Z. Chen, G. Kolhe, S. Rafatirad, S. D., H. Homayoun, L. Zhao, and C. Lu. CoRR, (2019)Architectural considerations for FPGA acceleration of machine learning applications in MapReduce.K. Neshatpour, H. Makrani, A. Sasan, H. Ghasemzadeh, S. Rafatirad, and H. Homayoun. SAMOS, page 89-96. ACM, (2018)Efficient utilization of adversarial training towards robust machine learners and its analysis.S. D., S. Amberkar, S. Rafatirad, and H. Homayoun. ICCAD, page 78. ACM, (2018)MEDIALIFE: from images to a life chronicle.A. Gupta, S. Rafatirad, M. Gao, and R. Jain. SIGMOD Conference, page 1119-1122. ACM, (2009)Event composition operators: ECO.S. Rafatirad, A. Gupta, and R. Jain. EIMM@MM, page 65-72. ACM, (2009)Pyramid: Machine Learning Framework to Estimate the Optimal Timing and Resource Usage of a High-Level Synthesis Design.H. Makrani, F. Farahmand, H. Sayadi, S. Bondi, S. Dinakarrao, L. Zhao, A. Sasan, H. Homayoun, and S. Rafatirad. CoRR, (2019)

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2SMaRT: A Two-Stage Machine Learning-Based Approach for Run-Time Specialized Hardware-Assisted Malware Detection.

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML 2SMaRT: A Two-Stage Machine Learning-Based Approach for Run-Time Specialized Hardware-Assisted Malware Detection.

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2SMaRT: A Two-Stage Machine Learning-Based Approach for Run-Time Specialized Hardware-Assisted Malware Detection.