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Education and Innovation in Embedded Systems Design

USI Università della Svizzera italiana, USI Faculty of Informatics, Advanced Learning and Research Institute USI Università della Svizzera italiana USI Faculty of Informatics USI Advanced Learning and Research Institute
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Author Title Type [ Year(Asc)]
2018
Pilato, C., and L. P. Carloni, "DarkMem: Fine-Grained Power Management of Local Memories for Accelerators in Embedded Systems", Proceedings of the Asia and South Pacific Design Automation Conference (ASPDAC), 2018.
Livi, L., F. Maria Bianchi, and C. Alippi, "Determination of the Edge of Criticality in Echo State Networks Through Fisher Information Maximization", IEEE Transactions on Neural Networks and Learning Systems, vol. 29, pp. 706-717, March, 2018.
Banik, S., A. Bogdanov, and F. Regazzoni, "Efficient Configurations for Block Ciphers with Unified ENC/DEC Paths", Proceedings of the IEEE International Symposium on Hardware Oriented Security and Trust (HOST) 2017, 2018.
Valencia, F., T. Oder, T. Güneysu, and F. Regazzoni, "Exploring the Vulnerability of R-LWE Encryption to Fault Attacks", Workshop on Cryptography and Security in Computing Systems of the HiPEAC2018 Conference, CS2 '18, New York, NY, USA, ACM, 2018.
Ferrante, A., M. Malek, F. Martinelli, F. Mercaldo, and J. Milosevic, "Extinguishing Ransomware - A Hybrid Approach to Android Ransomware Detection", Foundations and Practice of Security, vol. 10723, Cham, Springer International Publishing, pp. 242-258, 02/2018.
Kaitović, I., and M. Malek, "Impact of Failure Prediction on Availability: Modeling and Comparative Analysis of Predictive and Reactive Methods", IEEE Transactions on Dependable and Secure Computing, pp. 1-1, 2018.
Banik, S., A. Bogdanov, T. Isobe, H. Hiwatari, T. Akishita, and F. Regazzoni, "Inverse Gating for Low Energy Block Ciphers", Proceedings of the IEEE International Symposium on Hardware Oriented Security and Trust (HOST), 2018.
Bianchi, F. Maria, L. Livi, and C. Alippi, "Investigating echo state networks dynamics by means of recurrence analysis", IEEE Transactions on Neural Networks and Learning Systems, vol. 29, pp. 427 - 439, 02/2018.
Alippi, C., S. Disabato, and M. Roveri, "Moving Convolutional Neural Networks to Embedded Systems: The Alexnet and VGG-16 Case", Proceedings of the 17th ACM/IEEE International Conference on Information Processing in Sensor Networks, Piscataway, NJ, USA, IEEE Press, 2018.
Ferrante, A., "Panel IoT and pervasive computing: are new definitions of security and privacy needed?", Malicious Software and Hardware in Internet of Things Co-located with ACM International Conference on Computing Frontiers 2018, Ischia, Naples, Italy, 05/2018.
Bo, L., C. Alippi, and D. Zhao, "A Pdf-free Change Detection Test Based on Density Difference Estimation", IEEE Transactions on Neural Networks and Learning Systems, vol. 29, issue 2, pp. 324 - 334, 11/2016, 2018.
Regazzoni, F., A. Fowler, and I. Polian, "Quantum Era Challenges for Classical Computers", Proceedings of the 18th International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation, New York, NY, USA, ACM, 2018.
Mentens, N., E. Charbon, and F. Regazzoni, "Rethinking Secure FPGAs: TowardsCryptography-friendly Configurable Cell Architecture and its Automated Design Flow", Proceedings of FCCM, 05/2018.
Chaves, R., Ł. Chmielewski, F. Regazzoni, and L. Batina, "SCA-Resistance for AES: How Cheap Can We Go?", Progress in Cryptology – AFRICACRYPT 2018, Cham, Springer International Publishing, 2018.
Pilato, C., S. Garg, R. Karri, and F. Regazzoni, "Securing Hardware Accelerators: a New Challenge for High-Level Synthesis", IEEE Embedded Systems Letters, vol. 3, issue 10, pp. 77-80, 11/2017, 2018.
Regazzoni, F., C. Alippi, and I. Polian, "Security: The Dark Side of Approximate Computing?", Proceedings of the International Conference on Computer-Aided Design, New York, NY, USA, ACM, 11/2018.
Pilato, C., F. Regazzoni, R. Karri, and S. Garg, "TAO: Techniques for Algorithmic Obscuration during High-Level Synthesis", Proceedings of the ACM/IEEE Design Automation Conference (DAC), 2018.
Bianchi, F. Maria, L. Livi, A. Ferrante, J. Milosevic, and M. Malek, "Time series kernel similarities for predicting Paroxysmal Atrial Fibrillation from ECGs", IJCNN 2018 : International Joint Conference on Neural Networks, Rio, Brazil, IEEE, 07/2018.

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