【标题】Research on communication information hiding method of industrial internet of things based on deep fusion
【参考中译】基于深度融合的工业物联网通信信息隐藏方法研究
【类型】 期刊
【关键词】 information hiding; industrial internet of things communication; deep fusion; meter failure
【参考中译】 信息隐藏；工业物联网通信；深度融合；仪表故障
【作者】 Lin Tang
【摘要】 Traditional information hiding methods have the problems of high communication consumption and low encryption efficiency. This paper proposes a communication information hiding method of industrial internet of things based on deep fusion. Firstly, the Laplace mechanism is used to extract the networked differential privacy information. Secondly, the depth fusion method is used for homomorphic encryption of information ciphertext. Then, the encrypted ciphertext is obtained through key SK calculation, and the fog node for data transmission is generated to realise the replacement of communication information. Finally, deep fusion is used to realise the information hiding of industrial internet of things communication. The experimental results show that the maximum running time of meter encryption in this method is only 300 ms, and the communication consumption is no more than 0.58 bits, which shows that this method can improve the efficiency of meter encryption and reduce the communication energy consumption.
【参考中译】 传统的信息隐藏方法存在通信消耗大、加密效率低的问题。提出了一种基于深度融合的工业物联网通信信息隐藏方法。首先，利用拉普拉斯机制提取网络差异隐私信息。其次，采用深度融合方法对信息密文进行同态加密。然后，通过密钥SK计算得到加密密文，生成用于数据传输的雾节点，实现通信信息的替换。最后，利用深度融合技术实现了工业物联网通信中的信息隐藏。实验结果表明，该方法的表头加密最大运行时间仅为300ms，通信消耗不超过0.58bit，提高了表头加密的效率，降低了通信能耗。
【来源】 International Journal of Internet Manufacturing and Services 2022, vol.8, no.3
【入库时间】 2023/2/3
【标题】A stable data transmission method of industrial internet of things communication based on bat algorithm
【参考中译】一种基于BAT算法的工业物联网通信稳定数据传输方法
【关键词】 bat algorithm; industrial internet of things; remote communication; data transmission
【参考中译】 BAT算法；工业物联网；远程通信；数据传输
【作者】 YiPing Chen
【摘要】 Aiming at the problems of poor transmission stability and long transmission time in the traditional industrial internet of things communication data transmission, a stable transmission method of industrial internet of things communication data based on bat algorithm is designed. Firstly, build the industrial internet of things network model. Then, the sparse basis matrix is used to collect the communication data of industrial internet of things, and the noise in the communication data is removed by Gaussian function to complete the data extraction and preprocessing. Finally, the bat algorithm is used to determine the suitability of the location of the communication data, the updated data is transmitted in the optimised industrial internet of things communication network environment, and the differential genetic algorithm is used to suppress the interference factors to complete the stable data transmission. The results show that the proposed method can effectively improve the stability of communication data transmission.
【参考中译】 针对传统工业物联网通信数据传输稳定性差、传输时间长的问题，设计了一种基于BAT算法的工业物联网通信数据稳定传输方法。首先，构建工业物联网网络模型。然后，利用稀疏基矩阵对工业物联网通信数据进行采集，并用高斯函数去除通信数据中的噪声，完成数据的提取和预处理。最后，利用BAT算法确定通信数据的位置适宜性，将更新后的数据在优化后的工业物联网通信网络环境中传输，并使用差分遗传算法抑制干扰因素，完成稳定的数据传输。结果表明，该方法能有效提高通信数据传输的稳定性。
【标题】Using artificial intelligence technology to fight COVID-19: a review
【参考中译】用人工智能技术对抗新冠肺炎：综述
【关键词】 Artificial intelligence; COVID-19; Epidemic prevention and control; Internet of Things; Cloud computing; Blockchain; HEALTH-CARE; AI; PREDICTION; CLASSIFICATION; CHALLENGES; BLOCKCHAIN; PNEUMONIA; FRAMEWORK; SYSTEM; CHINA
【参考中译】 人工智能；新冠肺炎；疫情防控；物联网；云计算；区块链；医疗保健；AI；预测；分类；挑战；区块链；肺炎；框架；系统；中国
【作者】 Peng, Yong; Liu, Enbin; Peng, Shanbi; Chen, Qikun; Li, Dangjian; Lian, Dianpeng
【摘要】 In late December 2019, a new type of coronavirus was discovered, which was later named severe acute respiratory syndrome coronavirus 2(SARS-CoV-2). Since its discovery, the virus has spread globally, with 2,975,875 deaths as of 15 April 2021, and has had a huge impact on our health systems and economy. How to suppress the continued spread of new coronary pneumonia is the main task of many scientists and researchers. The introduction of artificial intelligence technology has provided a huge contribution to the suppression of the new coronavirus. This article discusses the main application of artificial intelligence technology in the suppression of coronavirus from three major aspects of identification, prediction, and development through a large amount of literature research, and puts forward the current main challenges and possible development directions. The results show that it is an effective measure to combine artificial intelligence technology with a variety of new technologies to predict and identify COVID-19 patients.
【参考中译】 2019年12月下旬，发现了一种新型冠状病毒，后来被命名为严重急性呼吸综合征冠状病毒2型(SARS-CoV-2)。自发现以来，该病毒已在全球蔓延，截至2021年4月15日，已有2975,875人死亡，并对我们的卫生系统和经济产生了巨大影响。如何抑制新型冠状肺炎的持续蔓延，是许多科学家和研究人员的主要任务。人工智能技术的引入为抑制新型冠状病毒提供了巨大贡献。本文通过大量的文献研究，从识别、预测、发展三大方面论述了人工智能技术在冠状病毒抑制中的主要应用，并提出了当前面临的主要挑战和可能的发展方向。结果表明，将人工智能技术与多种新技术相结合，是预测和识别新冠肺炎患者的有效措施。
【来源】 Artificial Intelligence Review: An International Science and Engineering Journal 2022, vol.55, no.6