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Research Abstract

There is undoubtedly a continuous growing security concern over the exposure of information and data during its entire life cycle. The high constant level of connectivity coupled with motion propagates unauthorized and malicious users both within and outside the organizations to access and monetize valuable information such as medical records, groove, intellectual properties, security secrets and national secrets among others.
In a global village where data is the currency, its confidentiality is very paramount. Data confidentiality is uncompromised both at motion and at rest, if it is accurate, complete and consistent (valid) throughout its entire lifecycle as envisaged by the owner globally (Ahmad et al., 2019). However, various bad actors have and continue to gain unauthorized access to both data in motion and at rest from embedded systems for nefarious activities.
Despite all the attempts to address security issues associated with data confidentiality, emergence of communication and networking technologies leveraged the idea of wireless embedded networks that either fully or partially rely on different types of embedded devices, providing them with a broader range of more ubiquitous applications which has resulted to more challenges, notably; the broadcast nature of the wireless radio signal which makes the embedded network extremely vulnerable to several networking threats (Xie et al., 2019).
This study intends to design a framework for data from car tracking embedded systems (Car Sensors) with enhanced confidentiality.

Key Words: Embedded Systems, Confidentiality, Internet of Things (IoT), Privacy, Data, Framework.