TY - JOUR
T1 - Security framework for IoT end nodes with neural networks
AU - Pacheco, Jesus
AU - Benitez, Victor H.
AU - Pan, Zhiwen
N1 - Publisher Copyright:
© 2008-2019. International Journal of Machine Learning and Computing.
PY - 2019/8/1
Y1 - 2019/8/1
N2 - The premise of the Internet of Things (IoT) is to connect not only computers and mobile devices, but also interconnect smart buildings, homes, and cities, as well as electrical and water grids, automobiles, and airplanes just to mention some examples. IoT leads to the development of a wide range of advanced information services that are pervasive, cost-effective, and can be accessed from anywhere and at any time. In this paper we present a multilayer architecture to integrate devices to the IoT, making it available from everywhere at any time. However, with the introduction of IoT we will be experiencing grand challenges to secure and protect its advanced information services due to the significant increase of the attack surface, complexity, heterogeneity,
AB - The premise of the Internet of Things (IoT) is to connect not only computers and mobile devices, but also interconnect smart buildings, homes, and cities, as well as electrical and water grids, automobiles, and airplanes just to mention some examples. IoT leads to the development of a wide range of advanced information services that are pervasive, cost-effective, and can be accessed from anywhere and at any time. In this paper we present a multilayer architecture to integrate devices to the IoT, making it available from everywhere at any time. However, with the introduction of IoT we will be experiencing grand challenges to secure and protect its advanced information services due to the significant increase of the attack surface, complexity, heterogeneity,
KW - Access control
KW - Internet of things
KW - Neural networks
KW - Threat detection
UR - http://www.scopus.com/inward/record.url?scp=85071307462&partnerID=8YFLogxK
U2 - 10.18178/ijmlc.2019.9.4.814
DO - 10.18178/ijmlc.2019.9.4.814
M3 - Artículo
AN - SCOPUS:85071307462
SN - 2010-3700
VL - 9
SP - 381
EP - 386
JO - International Journal of Machine Learning and Computing
JF - International Journal of Machine Learning and Computing
IS - 4
ER -