Nowadays, most robots and robotics platforms tend to deliver functionalities independently or other internet-connected devices. Hence, i.e. despite their pertinence and possible integration, IoT platforms and robots operate in isolation, which is a lost opportunity for a host of innovative functionalities. Security concerns are among the main barriers and concerns against the integration of IoT with smart semi-autonomous objects such as robots. In the scope of the SecureIoT socially assisted robots scenario, we demonstrate the secure integration of LuxAI’s QT robot(s) in an environment provided by iSPRINT’s CloudCare2U (CC2U) IoT healthcare platform, which holds the promise to enhance the functionalities offered by both QT and CC2U, while offering a host of business opportunities for both companies (LuxAI, iSPRINT). CC2U integrates a wide range of sensors and wearable devices (e.g., fibits, motion trackers) in order to accurate detect the users’ context and provide relevant personalized services. CC2U includes already a virtual robot as an output interface. As part of the scenario QT becomes CC2U’s interface for interaction with end-users. - Data Accuracy & Theft: Blackmailing, Espionage, etc. - Destruction of Environment: physical damage to the robots’ environment and psychological damage to human

1. Socially Assistive Robots Use
Case
07.12.2020This project has received funding from the European Union’s Horizon 2020 research and
innovation programme under grant agreement No 779899
LuxAI and iSprint

2. Socially Assistive
Robot
Robots are entering everyday lives of people
with various applications in healthcare and
education

3. Socially Assistive Robots – Security concerns
Social robots integrated in IoT environments
 Attack motivation:
 Data Theft:
 Blackmailing
 Espionage, etc.
 Destruction of Environment:
 physical damage to the robot
 physical and psychological
damage to humans. (Vandalism,
Terrorism, etc.)

4. Security concerns
and costs
Healthcare Domain

5. SecureIoT: Predictive Security for IoT-Enabled Socially Assistive Robots
Security solutions to observe, analyze and protect network of IoT
devices
Predictive Analytic (e.g anomaly detection)
Risk assessment and Mitigation
Compliance auditing
Programming supports
Market place : extending offered security services

6. SecureIoT Ambient Assisted Living Scenario
QTrobot in iSprint Smart Home
 Three scenarios have been implemented:
 Cognitive & coaching activity
 Monitoring & check-ups
 Daily Calendar & System Admin
 Different attacks and abuse cases:
 Man-in-the middle attack on data
exchanged between QTrobot and
cloud platforms
 DOS attack on cloud platforms
 Hijacking attack on robot
controllers
Coaching activities
Patient cognitive data
Patient Medical data

7. SecureIoT Ambient Assisted Living Scenario
SecureIoT Predictive Analytic Service
Man-in-the-middle
attack
DoS/DDoS
attack
Various types of attack at system and application levels are detected

8. SecureIoT Ambient Assisted Living Scenario
Risk Assessment Service
Different risk of attacks have been assessed
Man-in-the-middle
attack
DoS/DDoS
attack
Ransomware
attack
The assessment service can greatly help with
the understanding of the different cyber
securities risks at different level and their
potential mitigations.

9. SecureIoT Ambient Assisted Living Scenario
Compliance Auditing Service
 Auditing the existence of fine-grain logs
 Identification of potentially sensitive information
exchanges (GDPR)
 Auditing granular access controls
 Auditing the communications encryption and
authentications (NIST / ENISA)
 Auditing software modules privileges (GSMA).
More than 80% of
SAR critical assets
can be found in
Security
Knowledgebase

10. Thank you