Wireless body area networks play an indispensable role in the medical Internet of Things. It is a network of several wearables or implantable devices that use wireless technologies to communicate. These devices usually collect the wearer's physiological data and send it to the server. Some health care providers can access the server over the network and provide medical care to the wearer. Due to the openness and mobility of the wireless network, the adversary can easily steal and forge information, which exchanged in the communication channel that leaks wearer's privacy. Therefore, a secure and reliable authentication scheme is essential. Most of the existing authentication schemes are based on asymmetric encryption. However, since the sensor devices in wireless body area networks are typically resource-constrained devices, their computing resources cannot afford to use asymmetric encryption. In addition, most of the existing lightweight authentication schemes have various security vulnerabilities, especially the lack of forwarding secrecy. Therefore, we propose a secure lightweight authentication scheme for the wireless body area networks. With this scheme, forward secrecy can be guaranteed without using asymmetric encryption. We use the automatic security verification tool ProVerif to verify the security of our scheme and analyze informal security. The experimental results and the theoretical analysis indicate that our scheme significantly reduces the computational cost compared with the schemes using asymmetric encryption and that it has a lower security risk compared with the lightweight schemes. INDEX TERMS Authentication, IoT, security, wireless body area network.

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The log odds of positive lymph nodes (LODDS) was defined as the log of the ratio between the number of positive lymph nodes and the number of negative lymph nodes, which is a novel and promising nodal staging system for gastric cancer. Here, we aimed to compare the prognostic effect of pN, lymph node ratio (LNR) and LODDS. The association between overall survival and pN, LNR and LODDS was retrospectively analysed. The discriminatory ability and monotonicity of gradients (linear trend χ 2 score), homogeneity ability (likelihood ratio test) and prognostic stratification ability (Akaike information criterion [AIC] and receiver operating characteristic [ROC] curve) were compared among three lymph node staging systems. The pN, LNR and LODDS were all identified as independent prognostic factors for gastric cancer patients in the multivariate analysis. LODDS showed the best prognostic performance (linear trend χ 2 score 266.743, likelihood ratio χ 2 test score 427.771, AIC value 5670.226, area under the curve (AUC) 0.793), followed by LNR and pN. In patients with different levels of retrieved lymph nodes (≤10, 11–14, 15–25 and >25), LODDS was the most powerful for prognostic prediction and discrimination of the heterogeneity among the subgroups. Significant differences in survival were observed among patients in different LODDS subgroups after being classified according to the pN and LNR classifications. LODDS appears to be a more powerful system for predicting the overall survival of gastric cancer patients, as compared to LNR and pN, and may serve as an alternative nodal staging system for gastric cancer.

With the rapid advancement of video and image processing technologies in Internet-of-Things (IoT), it is urgent to address the issues in real-time performance, clarity and reliability of image recognition technique for monitoring system in foggy weather. In this work, a fast defogging image recognition algorithm is proposed based on bilateral hybrid filtering. Firstly, the mathematical model based on bilateral hybrid filtering is established. The dark channel is used for filtering and denoising the defogging image. After that, a bilateral hybrid filtering method can effectively improving the transmittance and robustness of images in defogging image by using a combination of guided filtering and median filtering. On this basis, the proposed algorithm greatly decreases the computation complexity of defogging image recognition and reduces the image execution time. Experimental results show that, the defogging effect and speed are encouraging. The image recognition rate reaches 98.8% after defogging.

With the advancement of information technology and the reduction of costs, the application of unmanned aerial vehicle (UAV) has gradually expanded from the military field to the industrial field and civilian field. It brings great convenience to people in surveillance, detection, transportation, emergency rescue etc. However, UAVs usually work in harsh natural environments, and their communication security confronts various challenges. Due to UAVs' limited resources, such as computing capability, storage space, and energy, traditional security protection schemes based on complex cryptographic algorithms are not suitable for UAV systems directly. Therefore, a two‐stage lightweight identity authentication and key agreement protocol for UAV is proposed in this paper. The entire process only uses hash and XOR operations, which significantly improves the authentication efficiency. Simultaneously, the physical unclonable function (PUF) is introduced and embedded into the UAV hardware to ensure UAV network communication security when a UAV suffers a physical capture attack. In the paper, the security of the proposed protocol is proved with Burrows–Abadi–Needham (BAN) logic, Real‐or‐Random (ROR) model, and AVISPA simulation tools. An informal security analysis is also provided to illustrate that the protocol satisfies the security requirements of UAV networks. Finally, the protocol is compared with other existing protocols regarding function properties, computation cost, and communication cost, which shows that the proposed protocol has effectiveness and practicality.

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Sensor nodes around monitoring area have various distances to the target node. Therefore, it is difficult to ensure security of broadcasting data transferred from a single wireless sensor node to base station. Multi-hop transmission of data between sensor nodes wastes network resource. In this case, a distributed data secure transmission scheme is proposed in a wireless sensor network. Data transmission is classified into two stages: constructing a collection of receiving nodes and selecting a unique forwarding node from this collection. These are implemented using analysis of relative movement distance between nodes and transfer time competitive mechanism. Besides, we have assumed a network model for distributed data secure transmission to improve efficiency of data transfer. This design includes secure model of node competition, data perception model, and anti-resistance model. Moreover, the security of competition transfer for nodes in wireless sensor network is evaluated. Finally, simulation proves that the proposed scheme has good performance in security and stability compared to similar schemes.

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