TY - JOUR
T1 - Network attack prediction method based on threat intelligence for IoT
AU - Zhang, Hongbin
AU - Yi, Yuzi
AU - Wang, Junshe
AU - Cao, Ning
AU - Duan, Qiang
N1 - Publisher Copyright:
© 2018, Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2019/11/1
Y1 - 2019/11/1
N2 - The Social Internet of Things (SIoT) is a combination of the Internet of Things (IoT) and social networks, which enables better service discovery and improves the user experience. The threat posed by the malicious behavior of social network accounts also affects the SIoT, this paper studies the analysis and prediction of malicious behavior for SIoT accounts, proposed a method for predicting malicious behavior of SIoT accounts based on threat intelligence. The method uses support vector machine (SVM) to obtain threat intelligence related to malicious behavior of target accounts, analyze contextual data in threat intelligence to predict the behavior of malicious accounts. By collecting and analyzing the data in a SIoT environment, verifies the malicious behavior prediction method of SIoT account proposed in this paper.
AB - The Social Internet of Things (SIoT) is a combination of the Internet of Things (IoT) and social networks, which enables better service discovery and improves the user experience. The threat posed by the malicious behavior of social network accounts also affects the SIoT, this paper studies the analysis and prediction of malicious behavior for SIoT accounts, proposed a method for predicting malicious behavior of SIoT accounts based on threat intelligence. The method uses support vector machine (SVM) to obtain threat intelligence related to malicious behavior of target accounts, analyze contextual data in threat intelligence to predict the behavior of malicious accounts. By collecting and analyzing the data in a SIoT environment, verifies the malicious behavior prediction method of SIoT account proposed in this paper.
UR - http://www.scopus.com/inward/record.url?scp=85058944031&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85058944031&partnerID=8YFLogxK
U2 - 10.1007/s11042-018-7005-2
DO - 10.1007/s11042-018-7005-2
M3 - Article
AN - SCOPUS:85058944031
SN - 1380-7501
VL - 78
SP - 30257
EP - 30270
JO - Multimedia Tools and Applications
JF - Multimedia Tools and Applications
IS - 21
ER -