Visible to the public An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor Analytics

TitleAn IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor Analytics
Publication TypeJournal Article
Year of Publication2017
AuthorsConti, F., Schilling, R., Schiavone, P. D., Pullini, A., Rossi, D., Gürkaynak, F. K., Muehlberghuber, M., Gautschi, M., Loi, I., Haugou, G., Mangard, S., Benini, L.
JournalIEEE Transactions on Circuits and Systems I: Regular Papers
Keywordsapproximate computing, CNN, compute-intensive data processing, Computer architecture, computerised instrumentation, cryptography, Data analysis, Data security, deep convolutional neural network, electroencephalogram, encrypted data collection, Encryption, energy 3.16 pJ, energy conservation, Engines, equivalent reduced instruction set computer operation, Face detection, feature extraction, Fulmine tight power envelope, Internet of Things, Internet-of-Things endpoint, IoT endpoint system-on-chip, low-power electronics, Metrics, Multicore Computing, multicore computing security, near-sensor data analytics pipeline, Neural networks, parallel architectures, pubcrawl, regular computing task, remote recognition, resilience, Resiliency, Scalability, secure autonomous aerial surveillance, security of data, seizure detection, sensitive data protection, Sensors, size 65 nm, SoC, software programmability, system-on-chip, tightly-coupled multicore cluster, voltage 0.8 V

Near-sensor data analytics is a promising direction for internet-of-things endpoints, as it minimizes energy spent on communication and reduces network load - but it also poses security concerns, as valuable data are stored or sent over the network at various stages of the analytics pipeline. Using encryption to protect sensitive data at the boundary of the on-chip analytics engine is a way to address data security issues. To cope with the combined workload of analytics and encryption in a tight power envelope, we propose Fulmine, a system-on-chip (SoC) based on a tightly-coupled multi-core cluster augmented with specialized blocks for compute-intensive data processing and encryption functions, supporting software programmability for regular computing tasks. The Fulmine SoC, fabricated in 65-nm technology, consumes less than 20mW on average at 0.8V achieving an efficiency of up to 70pJ/B in encryption, 50pJ/px in convolution, or up to 25MIPS/mW in software. As a strong argument for real-life flexible application of our platform, we show experimental results for three secure analytics use cases: secure autonomous aerial surveillance with a state-of-the-art deep convolutional neural network (CNN) consuming 3.16pJ per equivalent reduced instruction set computer operation, local CNN-based face detection with secured remote recognition in 5.74pJ/op, and seizure detection with encrypted data collection from electroencephalogram within 12.7pJ/op.

Citation Keyconti_iot_2017