@Article{jiot.2020.010035,
AUTHOR = {Bichen Che, Long Liu, Huali Zhang},
TITLE = {KNEMAG: Key Node Estimation Mechanism Based on Attack Graph for IoT  Security},
JOURNAL = {Journal on Internet of Things},
VOLUME = {2},
YEAR = {2020},
NUMBER = {4},
PAGES = {145--162},
URL = {http://www.techscience.com/jiot/v2n4/40248},
ISSN = {2579-0080},
ABSTRACT = {With the rapid development and widespread application of the IoT, 
the at-tacks against IoT vulnerabilities have become more complex and diverse. 
Most of the previous research focused on node vulnerability and its risk analysis. 
There is little information available about the importance of the location of the 
node in the system. Therefore, an estimation mechanism is proposed to assess the 
key node of the IoT system. The estimation of the key node includes two parts: 
one is the utilization relationship between nodes, and the other is the impact on 
the system after the node is conquered. We use the node importance value and 
the node risk value to quantify these two parts. First, the node importance value 
is calculated by considering the attack path that pass through the node and the 
probability that the attacker will abandon the attack. Second, in addition to node 
vulnerabilities and the consequences of being attacked, two quantitative 
indicators are proposed to comprehensively assess the impact of nodes on the 
system security, and the node risk value is calculated based on the grey 
correlation analysis method. Third, the key node in the IoT system could be 
obtained by integrating the node importance value and risk value. Finally, the 
simulation experiment result shows that the presented method could find the key 
node of the system quickly and accurately.},
DOI = {10.32604/jiot.2020.010035}
}