Enabling Security Services in Socially Assistive Robot Scenarios for Healthcare Applications

Area of Science:

• Cybersecurity
• Internet of Things (IoT)
• Robotics
• Healthcare Technology

Background:

• Modern IoT deployments are complex and heterogeneous, presenting significant security challenges.
• Existing security solutions often lack end-to-end support, cross-platform interoperability, and ease of application for practitioners.
• Scalable, decentralized, and intelligent security mechanisms are crucial for addressing these IoT security gaps.

Purpose of the Study:

• To define, implement, and validate a SecureIoT-enabled usage scenario for socially assisted robots (SAR).
• To integrate and assess SecureIoT services within personalized healthcare and ambient assistive living (AAL) contexts.
• To demonstrate the application of SecureIoT in enhancing security for integrated AAL platforms like QTrobot (QT) and CloudCare2U (CC2U).

Main Methods:

• Conducted risk assessment of communication security within the SAR scenario.
• Implemented predictive analysis for identifying potential security risks.
• Applied access control policies and audited the solution against security, safety, and privacy guidelines.

Main Results:

• Successfully integrated and validated SecureIoT services within a practical SAR usage scenario.
• Demonstrated enhanced security through risk assessment, predictive analysis, access control, and auditing.
• Provided a foundation for securing personalized healthcare and AAL environments using advanced IoT security.

Conclusions:

• The SecureIoT framework offers a viable solution for addressing security challenges in complex IoT environments.
• The SAR usage scenario effectively demonstrates the integration and benefits of SecureIoT services in healthcare applications.
• Future work includes extending this security paradigm to integrate healthcare platforms with broader IoT solutions via product assurance processes.