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Lightweight Node-level Malware Detection and Network-level Malware Confinement in IoT Networks.

S. Dinakarrao, H. Sayadi, H. Makrani, C. Nowzari, S. Rafatirad, and H. Homayoun. DATE, page 776-781. 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)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)Lightweight Node-level Malware Detection and Network-level Malware Confinement in IoT Networks.S. Dinakarrao, H. Sayadi, H. Makrani, C. Nowzari, S. Rafatirad, and H. Homayoun. DATE, page 776-781. IEEE, (2019)XPPE: cross-platform performance estimation of hardware accelerators using machine learning.H. Makrani, H. Sayadi, T. Mohsenin, S. Rafatirad, A. Sasan, and H. Homayoun. ASP-DAC, page 727-732. ACM, (2019)Advances and throwbacks in hardware-assisted security: special session.F. Brasser, L. Davi, A. Dhavlle, T. Frassetto, S. Dinakarrao, S. Rafatirad, A. Sadeghi, A. Sasan, H. Sayadi, S. Zeitouni and 1 other author(s). CASES, page 15:1-15:10. ACM, (2018)Comprehensive assessment of run-time hardware-supported malware detection using general and ensemble learning.H. Sayadi, S. D., A. Houmansadr, S. Rafatirad, and H. Homayoun. CF, page 212-215. ACM, (2018)System and Architecture Level Characterization of Big Data Applications on Big and Little Core Server Architectures.M. Malik, S. Rafatirad, and H. Homayoun. ACM Trans. Model. Perform. Evaluation Comput. Syst., 3 (3): 14:1-14:32 (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)

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Lightweight Node-level Malware Detection and Network-level Malware Confinement in IoT Networks.

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Lightweight Node-level Malware Detection and Network-level Malware Confinement in IoT Networks.

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Lightweight Node-level Malware Detection and Network-level Malware Confinement in IoT Networks.