Dynamic Aging Weight Scheme for Trust Model in Internet of Medical Things
Weidong Fang, Chunsheng Zhu, Tian Min Ma, Wuxiong Zhang, Baoqing Li, Yi Li, Fangchen Xu, Tianchen Zhang, Bo Wang · 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · 2021
It has been observed that the Internet of Medical Things (IoMT) is being deployed to construct varieties of intelligent platforms in medical and healthcare field, in order to comprehensively improve the quality of medical services. However, the cyber security of IoMT is facing enormous threat. Although many trust schemes are proposed to address the issue, the ignorance of aging weight in trust increases the risk of long-term attacks before being detected. In this paper, we design a dynamic aging weight scheme for trust model in IoMT. Essentially, when there are cooperative behaviors between two nodes, the aging weight can be set as large as possible to slow down the increase in the trust value of normal nodes. Once noncooperative behaviors appear, the smaller aging weight could mitigate the danger of compromised nodes. The simulation results indicate that our proposed scheme could better meet the principle of “Easy to lose” for trust.