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A New Private Information Encryption Method in Internet of Things under Cloud Computing Environment

机译:云计算环境下的新私人信息加密方法

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摘要

The existence of Internet of Things (IoT) facilitates the collection and transmission of urban data information. However, it can leak users’ personal privacy information in smart cities. Therefore, we propose a new private information encryption method in IoT under cloud computing environment. Under IoT, according to the properties and acquisition time, privacy information can be divided into many subspaces. Then, we analyze the private information encryption with different levels. Based on the stream cipher mechanism, we design an encryption system model of information collection. In the subspace, the privacy information is encrypted and transferred to the relay node. After encrypting, they are segmented and restructured. The long privacy information is divided into smaller slices. Then, they are reintegrated after conversion. Finally, we use stream cipher and dual-key algorithm to complete freedom nondestructive transformation between plaintext and ciphertext to ensure the integrity of the encrypted private information. Experimental results show that the proposed method takes less time in the encryption and decryption process, which has better ciphertext conversion output effect and suffers fewer network attacks in the same encryption time. The message encryption and decryption time is less than that of other methods. In terms of calculation cost, the proposed method decreases by approximately 14%. What is more, it has higher security and improves the security and integrity of the privacy information collection process.
机译:物联网(物联网)的存在促进了城市数据信息的收集和传输。但是,它可以在智能城市中泄漏用户的个人隐私信息。因此,我们在云计算环境下提出了一种新的私人信息加密方法。根据物资料,根据属性和收购时间,隐私信息可以分为许多子空间。然后,我们分析具有不同级别的私人信息加密。基于流密码机制,我们设计了信息集的加密系统模型。在子空间中,隐私信息被加密并传输到中继节点。加密后,它们被分段并重组。长隐私信息分为较小的切片。然后,转换后重新融入。最后,我们使用流密码和双键算法来完成明文和密文之间的自由无损转换,以确保加密的私人信息的完整性。实验结果表明,该方法在加密和解密过程中需要更少的时间,这具有更好的密文转换输出效果,并且在相同的加密时间内遭受更少的网络攻击。消息加密和解密时间小于其他方法。在计算成本方面,所提出的方法减少了大约14%。更重要的是,安全性更高,提高了隐私信息收集过程的安全性和完整性。

著录项

  • 作者

    Haiyun Ma; Zhonglin Zhang;

  • 作者单位
  • 年度 2020
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  • 原文格式 PDF
  • 正文语种 eng
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