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引用次数: 0

摘要

边缘计算的现状是不同的计算能力通过各种各样的通信路径连接的环境。这种形势既创造了巨大的作战能力机遇,也带来了难以想象的安全问题。本文强调,识别安全威胁并开发技术和策略来防御该威胁的传统安全方法已不再适用。各种各样的安全级别、计算能力和通信渠道需要一种学习、响应、多样化和个性化的信息安全方法。我们描述了基于关系、历史、信任状态、请求操作和结果响应选择的安全方面的事务性质分类。问题是,参与边缘计算的每对设备之间的信任评估必须个性化。我们建议边缘计算世界中的每个元素利用本地化能力与与该元素通信的每个实体建立自适应学习信任模型。具体来说,我们提出的模型基于每次交互增加或减少信任得分的值。
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Security Considerations for Edge Computing
Present state of edge computing is an environment of different computing capabilities connecting via a wide variety of communication paths. This situation creates both great operational capability opportunities and unimaginable security problems. This paper emphasizes that the traditional approaches to security of identifying a security threat and developing the technology and policies to defend against that threat are no longer adequate. The wide variety of security levels, computational capabilities, and communication channels requires a learning, responsive, varied, and individualized approach to information security. We describe a classification of the nature of transactions with respect to security based upon relationships, history, trust status, requested actions and resulting response choices. Problem is that the trust evaluation has to be individualized between each pair of devices participating in edge computing. We propose that each element in the edge computing world utilizes a localized ability to establish an adaptive learning trust model with each entity that communicates with the element. Specifically, the model we propose increments or decrements the value of trust score based upon each interaction.
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