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arXiv 2104.00634cs.CRcs.SE
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IoT中的安全性和机器学习采用:IoT开发人员讨论的初步研究

Security and Machine Learning Adoption in IoT: A Preliminary Study of IoT Developer Discussions

Gias Uddin

摘要:

物联网(IoT)被定义为地点和物理对象之间的连接(即,事物)经由智能计算设备通过因特网/网络。传统上,我们通过对物联网开发人员/从业人员进行调查来了解物联网生态系统/问题。另一种学习方法是分析流行的在线开发者论坛(如Stack Overflow(SO))中的物联网开发者讨论。然而,我们知道没有这样的研究,专注于物联网开发人员的安全性和ML相关的讨论在SO。本文提供了SO中物联网开发人员讨论的初步研究结果。我们发现大约12%的句子包含安全讨论,而大约0.12%的句子包含ML相关的讨论。我们发现,物联网开发人员在讨论安全问题时经常询问如何在物联网设备和用户之间安全地存储、共享和传输共享数据。我们还发现,物联网开发人员有兴趣将基于深度神经网络的ML模型应用到他们的物联网设备中,但他们发现将这些模型应用到资源受限的物联网设备中具有挑战性。我们的研究结果为物联网供应商和研究人员开发和设计新技术以提高物联网设备的安全性和ML采用提供了启示。

英文摘要:

Internet of Things (IoT) is defined as the connection between places and physical objects (i.e., things) over the internet/network via smart computing devices. Traditionally, we learn about the IoT ecosystem/problems by conducting surveys of IoT developers/practitioners. Another way to learn is by analyzing IoT developer discussions in popular online developer forums like Stack Overflow (SO). However, we are aware of no such studies that focused on IoT developers' security and ML-related discussions in SO. This paper offers the results of preliminary study of IoT developer discussions in SO. We find around 12% of sentences contain security discussions, while around 0.12% sentences contain ML- related discussions. We find that IoT developers discussing security issues frequently inquired about how the shared data can be stored, shared, and transferred securely across IoT devices and users. We also find that IoT developers are interested to adopt deep neural network-based ML models into their IoT devices, but they find it challenging to accommodate those into their resource-constrained IoT devices. Our findings offer implications for IoT vendors and researchers to develop and design novel techniques for improved security and ML adoption into IoT devices.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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