Machine learning based solutions for security of Internet of Things (IoT): A survey

SM Tahsien, H Karimipour, P Spachos - Journal of Network and Computer …, 2020 - Elsevier
Over the last decade, IoT platforms have been developed into a global giant that grabs every
aspect of our daily lives by advancing human life with its unaccountable smart services …

A survey of machine and deep learning methods for internet of things (IoT) security

MA Al-Garadi, A Mohamed, AK Al-Ali… - … surveys & tutorials, 2020 - ieeexplore.ieee.org
The Internet of Things (IoT) integrates billions of smart devices that can communicate with
one another with minimal human intervention. IoT is one of the fastest develo** fields in …

Internet of Things: A survey on machine learning-based intrusion detection approaches

KAP Da Costa, JP Papa, CO Lisboa, R Munoz… - Computer Networks, 2019 - Elsevier
In the world scenario, concerns with security and privacy regarding computer networks are
always increasing. Computer security has become a necessity due to the proliferation of …

FEMa: A finite element machine for fast learning

DR Pereira, MA Piteri, AN Souza, JP Papa… - Neural Computing and …, 2020 - Springer
Abstract Machine learning has played an essential role in the past decades and has been in
lockstep with the main advances in computer technology. Given the massive amount of data …

Performance analysis of electricity theft detection for the smart grid: An overview

Z Yan, H Wen - IEEE Transactions on Instrumentation and …, 2021 - ieeexplore.ieee.org
Electricity theft has been a growing concern for the smart grid. It can be defined as follows:
illegal customers use energy from electric utilities without a contract or manipulate their …

Hybrid of anomaly-based and specification-based IDS for Internet of Things using unsupervised OPF based on MapReduce approach

H Bostani, M Sheikhan - Computer Communications, 2017 - Elsevier
Abstract Internet of Things (IoT) is a novel paradigm in computer networks in which resource-
constrained objects connect to unreliable Internet by using a wide range of technologies …

Review of various modeling techniques for the detection of electricity theft in smart grid environment

T Ahmad, H Chen, J Wang, Y Guo - Renewable and Sustainable Energy …, 2018 - Elsevier
This review paper focuses on the various modeling practices for the identification and
apprehension of non-technical losses. The modeling practices are extremely vital to …

Efficient supervised optimum-path forest classification for large datasets

JP Papa, AX Falcao, VHC De Albuquerque… - Pattern Recognition, 2012 - Elsevier
Today data acquisition technologies come up with large datasets with millions of samples for
statistical analysis. This creates a tremendous challenge for pattern recognition techniques …

Keratoconus severity identification using unsupervised machine learning

S Yousefi, E Yousefi, H Takahashi, T Hayashi… - PLoS …, 2018 - journals.plos.org
We developed an unsupervised machine learning algorithm and applied it to big corneal
parameters to identify and monitor keratoconus stages. A big dataset of corneal swept …

Intrusion detection systems for RPL security: a comparative analysis

G Simoglou, G Violettas, S Petridou, L Mamatas - Computers & Security, 2021 - Elsevier
Abstract Internet of Things (IoT) is an emerging technology that has seen remarkable
blossom over the last years. The growing interest for IPv6 constrained networks has made …