Although the Trans-Himalayan region (THR) is an important endemic and rendezvous area of peste des petits ruminants (PPR), monitoring and prevention measurements are difficult to execute because of the rough geographical conditions. Besides, a heterogeneous breeding system and the poor veterinary service of susceptible animals compound the existing problems. Here, we propose a forecasting system to define the key points of PPR prevention and aid the countries in saving time, labor, and products to achieve the goal of the global eradication project of PPR. The spatial distribution of PPR was predicted in the THR for the first time using a niche model that was constructed with a combination of eco-geographical, anthropoid, meteorological, and host variables. The transboundary least-cost paths (LCPs) of small ruminants in the THR were also calculated. Our results reveal that the low-elevation area of the THR had a higher PPR risk and was mainly dominated by human variables. The high-elevation area had lower risk and was mainly dominated by natural variables. Eight LCPs representing corridors among India, Nepal, Bhutan, Bangladesh, and China were obtained. This confirmed the potential risk of transboundary communication by relying on PPR contamination on the grasslands for the first time. The predicted potential risk communication between the two livestock systems and landscapes (high and low elevation) might play a role in driving PPR transboundary transmission.
With the widespread use of fog-to-cloud computing–based Internet of things devices, how to ensure the integrity of the data uploaded to the cloud has become one of the most important security issues. This article proposes an efficient and secure data auditing scheme based on fog-to-cloud computing for Internet of things scenarios, which can better meet performance and security requirements. The proposed scheme realizes data sharing under the condition of protecting privacy by encrypting sensitive information. Using the private key separation method, the private key is divided into two parts using identity information generation and random selection which are, respectively, held by the user and the fog center. Then, using the two-time signature method, the Internet of things and fog computing center use two parts of the private key to generate the original signature and final signature in two separate times. Since the fog computing center only has a part of the private key generated using the identity information, the security of the system will not be damaged due to the leakage of part of the private key held by the fog center, and the fog center significantly participates in the signature generation process, which significantly reduces the computation and communication overhead of the Internet of things device. Security analysis and performance evaluation show that the proposed scheme is safe and efficient.
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