VASERP: An Adaptive, Lightweight, Secure, and Efficient RFID-Based Authentication Scheme for IoV.

With the rapid growth in wireless communication and IoT technologies, Radio Frequency Identification (RFID) is applied to the Internet of Vehicles (IoV) to ensure the security of private data and the accuracy of identification and tracking. However, in traffic congestion scenarios, frequent mutual authentication increases the overall computing and communication overhead of the network. For this reason, in this work, we propose a lightweight RFID security fast authentication protocol for traffic congestion scenarios, designing an ownership transfer protocol to transfer access rights to vehicle tags in non-congestion scenarios. The edge server is used for authentication, and the elliptic curve cryptography (ECC) algorithm and the hash function are combined to ensure the security of vehicles' private data. The Scyther tool is used for the formal analysis of the proposed scheme, and this analysis shows that the proposed scheme can resist typical attacks in mobile communication of the IoV. Experimental results show that, compared to other RFID authentication protocols, the calculation and communication overheads of the tags proposed in this work are reduced by 66.35% in congested scenarios and 66.67% in non-congested scenarios, while the lowest are reduced by 32.71% and 50%, respectively. The results of this study demonstrate a significant reduction in the computational and communication overhead of tags while ensuring security.

Evaluation of different surgical dressings in reducing postoperative surgical site infection of a closed wound: A network meta-analysis.

OBJECTIVE: To evaluate the effects of different surgical dressings in reducing surgical site infection (SSI) and identify the optimal dressings. METHODS: Randomized controlled trials investigating the application of surgical dressings were retrieved from electronic databases, including MEDLINE, EMBASE, and the Cochrane Library. The odds ratios (ORs) of the SSI rate were compared by direct meta-analysis, and the surface under the cumulative ranking (SUCRA) curve values were calculated based on the Bayesian theorem. A node-splitting model was applied to analyse the consistency of the comprehensive comparison results. RESULTS: Twenty-two studies containing 5487 participants were pooled for the comprehensive comparison. Among all the studies included, 9 types of surgical dressings were identified for comparison. The results of the direct meta-analysis revealed that novel dressings significantly reduced the overall SSI rate with an OR of 1.026 (95% CI: 1.013-1.040, p < 0.001), which was determined to have low heterogeneity (I2 = 32.1%). Specifically, 3 types of dressings presented significant effects in reducing SSI, namely, mupirocin-containing (OR = 1.076, 95% CI: 1.014-1.142, p = 0.015), dialkylcarbamoyl-chloride-containing (OR = 1.047, 95% CI: 1.012-1.083, p = 0.008) and vitamin E (VE)-silicone-containing (OR = 1.129, 95% CI: 1.016-1.255, p = 0.025) dressings. Network meta-analysis demonstrated that the VE-silicone dressing (SUCRA = 0.37) was the optimal dressing, followed by the mupirocin dressing, with a SUCRA of 0.31. CONCLUSION: The present network meta-analysis identified the superiority of VE-silicone and mupirocin dressings in preventing SSI. The evidence-based results provide suggestions and directions for future investigations on surgical dressings. More large-scale trials with rigorous designs are warranted to clarify the clinical value of novel dressings in surgical incision management.