A Deep Learning approach to Privacy Preservation in Assisted Living
In the era of IoT technologies the potential for privacy invasion is becoming a major concern especially in regards to healthcare data and Ambient Assisted Living (AAL) environments. The need for sharing of healthcare data between various systems and stakeholders is growing rapidly. Systems that offer AAL technologies make extensive use of personal data in order to provide services that are context-aware and personalized. This makes privacy preservation a very important issue especially since the users are not always aware of the privacy risks they could face. A lot of progress has been made in the deep learning field, however, there has been lack of research on privacy preservation of sensitive personal data with the use of deep learning. In this paper we focus on an Long Short Term Memory (LSTM) Encoder-Decoder, which is a principal component of deep learning, and propose a new encryption technique that allows the creation of different AAL data views, depending on the access level of the end user and the information they require access to.
Citation : Psychoula, I. et al. (2018) A Deep Learning approach to Privacy Preservation in Assisted Living, Percom2018, SmartAAL workshop, Athens, March 2018.
Research Group : CIIRG
Research Institute : Cyber Technology Institute (CTI)
Peer Reviewed : Yes