Secure Embedded Living: Towards A Self-Contained User Data Preserving Framework

Somnath Mazumdar, Thomas Dreibholz

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Smart living represents the hardware-software co-habiting with humans for better living standards and improved well being. Here, hardware monitors human activities (by collecting data) specific to a context. Such data can be processed to offer valuable context-specific insights. Such insights can be used for optimizing the well being, living experience, and energy cost of smart homes. This article proposes the Secure Embedded Living Framework (SELF), which enforces a privacy-preserving data control mechanism by integrating multiple technologies, such as the Internet of Things, cloud/fog platform, machine learning, and blockchain. The primary aim of SELF is to allow the user to retain more control of its data.
TidsskriftIEEE Communications Magazine
Udgave nummer11
Sider (fra-til)74-80
Antal sider7
StatusUdgivet - nov. 2022


  • Cloud computing
  • Costs
  • Smart homes
  • Machine learning
  • Hardware
  • Blockchains
  • Internet of things