TY - JOUR
T1 - Signature gateway
T2 - Offloading signature generation to IoT gateway accelerated by GPU
AU - Chang, Chin Chen
AU - Lee, Wai Kong
AU - Liu, Yanjun
AU - Goi, Bok Min
AU - Phan, Raphael C.W.
N1 - Funding Information:
Manuscript received May 14, 2018; revised August 19, 2018 and October 14, 2018; accepted November 3, 2018. Date of publication November 15, 2018; date of current version June 19, 2019. This research work was partly supported by the Universiti Tunku Abdul Rahman Research Fund (UTARRF) with Project Number IPSR/RMC/UTARRF/2016-C2/L04. (Corresponding author: Chin-Chen Chang.) C.-C. Chang and Y. Liu are with the Department of Information Engineering and Computer Science, Feng Chia University, Taichung 407, Taiwan (e-mail: [email protected]; [email protected]).
Publisher Copyright:
© 2014 IEEE.
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2019/6
Y1 - 2019/6
N2 - The emergence of Internet of Things (IoT) brings us the possibility to form a well connected network for ubiquitous sensing, intelligent analysis, and timely actuation, which opens up many innovative applications in our daily life. To secure the communication between sensor nodes, gateway devices and cloud servers, cryptographic algorithms (e.g., digital signature, block cipher, and hash function) are widely used. Although cryptographic algorithms are effective in preventing malicious attacks, they involve heavy computation that may not be executed efficiently in resource constraint sensor nodes. In particular, the authentication of a sensor node is usually performed through a digital signature (e.g., RSA and elliptic curve cryptography), which can be slow when executed on a microcontroller. In this paper, an IoT architecture that offloads the digital signature generation to a nearby signature gateway equipped with graphic processing unit (GPU) accelerator are proposed. The communication process for signature offloading, together with optimized implementation techniques for RSA in signature gateway, are also presented in this paper. We have evaluated two different ways to implement modular exponentiation in RSA, namely residue number system and multiprecision montgomery multiplication (MPMM). The experimental results show that our RSA implementation using MPMM is 10.1% faster than the best RSA implementation in GPU. Our proposed IoT architecture with signature gateway can successfully reduce the burden of sensor nodes to generate signatures, at the same time preserve the ability to authenticate the sensor nodes.
AB - The emergence of Internet of Things (IoT) brings us the possibility to form a well connected network for ubiquitous sensing, intelligent analysis, and timely actuation, which opens up many innovative applications in our daily life. To secure the communication between sensor nodes, gateway devices and cloud servers, cryptographic algorithms (e.g., digital signature, block cipher, and hash function) are widely used. Although cryptographic algorithms are effective in preventing malicious attacks, they involve heavy computation that may not be executed efficiently in resource constraint sensor nodes. In particular, the authentication of a sensor node is usually performed through a digital signature (e.g., RSA and elliptic curve cryptography), which can be slow when executed on a microcontroller. In this paper, an IoT architecture that offloads the digital signature generation to a nearby signature gateway equipped with graphic processing unit (GPU) accelerator are proposed. The communication process for signature offloading, together with optimized implementation techniques for RSA in signature gateway, are also presented in this paper. We have evaluated two different ways to implement modular exponentiation in RSA, namely residue number system and multiprecision montgomery multiplication (MPMM). The experimental results show that our RSA implementation using MPMM is 10.1% faster than the best RSA implementation in GPU. Our proposed IoT architecture with signature gateway can successfully reduce the burden of sensor nodes to generate signatures, at the same time preserve the ability to authenticate the sensor nodes.
KW - Cryptography
KW - Digital signature
KW - Graphic processing unit (GPU)
KW - Internet of Things (IoT)
KW - Residue number system (RNS)
UR - http://www.scopus.com/inward/record.url?scp=85056577484&partnerID=8YFLogxK
U2 - 10.1109/JIOT.2018.2881425
DO - 10.1109/JIOT.2018.2881425
M3 - Article
AN - SCOPUS:85056577484
SN - 2327-4662
VL - 6
SP - 4448
EP - 4461
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
IS - 3
ER -