
doi: 10.52953/gytk2455
The widespread adoption of Internet of Things (IoT) applications in different technical fields has resulted in a significant increase in connected devices while amplifying concerns regarding security and privacy. The presence of security vulnerabilities in various layers of IoT design has emerged as an important issue. Trusted computing, particularly leveraging the Trusted Platform Module (TPM), is seen as a promising approach to counter these vulnerabilities. This paper investigates thoroughly the utilization of TPM technology to enhance node authentication with a focus on energy efficiency. Researchers closely examine each layer to carefully outline an adversary model that is tailored to the IoT ecosystem. The node authentication scheme that is proposed leverages TPM, which has advantages both in terms of processing time and energy. The outcome of this study can be applied to Flying AdHoc Network (FANET) nodes that operate in areas with high levels of traffic, where there are strict safety and reliability standards. Experiments conducted present the essential significance of TPM in ensuring secure node authentication across various application environments. The adoption of TPM technology is validated through rigorous performance assessments, revealing significant improvements in both energy efficiency and security.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 2 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
