Open AccessAn Improved Information Security Risk Assessments Method for Cyber-Physical-Social Computing and Networking
Author(s) -
Senyu Li,
Fangming Bi,
Wei Chen,
Xuzhi Miao,
Jin Liu,
Chaogang Tang
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2018.2800664
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
In virtue of the rapid development of the Internet of Things (IoT), Organizations have grown to rely on their cyber systems and networks. However, this phenomenon also creates many new information security issues. In this paper, we propose an evolutionary algorithm improved cuckoo search (ICS) to pretrain a backpropagation neural network (BPNN) for the sake of improving the accuracy and stability. Using this pre-training process, the BPNN can surmount the defect of falling into the local minima and greatly improve its efficiency. Then, this neural network is used as a part of information security risk assessment (ISRA) processes for a miniature IoT system. An illustration example is introduced to demonstrate that the ICS-BPNN outperforms other neural networks in this ISRA process.
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