An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor Analytics

IEEE Transactions on Circuits and Systems I: Regular Papers

Volumn 64, Issue 9, 2017, Pages 2481-2494

  Conti, Francesco ^a,b   Schilling, Robert ^c,d   Schiavone, Pasquale Davide ^a   Pullini, Antonio ^a   Rossi, Davide ^b   Gurkaynak, Frank Kagan ^a   Muehlberghuber, Michael ^a   Gautschi, Michael ^a   Loi, Igor ^b   Haugou, Germain ^a   Mangard, Stefan ^c   Benini, Luca ^a,b  

^a ETH ZURICH   (Switzerland)

^b UNIVERSITY OF BOLOGNA   (Italy)

^c GRAZ UNIVERSITY OF TECHNOLOGY   (Austria)

^d KNOW CENTER   (Austria)

Author keywords

approximate computing; Computer architecture; encryption; feature extraction; Internet of Things; low power electronics; neural networks; parallel architectures

Indexed keywords

ANTENNAS; APPLICATION SPECIFIC INTEGRATED CIRCUITS; CLUSTER COMPUTING; COMPUTER ARCHITECTURE; CONVOLUTION; CONVOLUTIONAL NEURAL NETWORKS; CRYPTOGRAPHY; DATA ANALYTICS; DEEP NEURAL NETWORKS; ENERGY EFFICIENCY; FACE RECOGNITION; FEATURE EXTRACTION; INTERNET OF THINGS; LOW POWER ELECTRONICS; NETWORK ARCHITECTURE; NEURAL NETWORKS; PARALLEL ARCHITECTURES; PROGRAMMABLE LOGIC CONTROLLERS; SYSTEM-ON-CHIP;

65-NM TECHNOLOGIES; AERIAL SURVEILLANCE; APPROXIMATE COMPUTING; ENCRYPTION FUNCTION; FLEXIBLE APPLICATIONS; MULTI-CORE CLUSTER; REDUCED INSTRUCTION SET COMPUTERS; SYSTEM ON CHIPS (SOC);

NETWORK SECURITY;

EID: 85018909901     PISSN: 15498328     EISSN: 15580806     Source Type: Journal    
DOI: 10.1109/TCSI.2017.2698019     Document Type: Article

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