Intelligent Management of Industrial IoT Bill Karakostas, VLTN

1. CHARIOT-VESSEDIA Workshop “THE ROAD AHEAD FOR A COGNITIVE COMPUTING PLATFORM SUPPORTING A UNIFIED APPROACH TOWARDS PRIVACY, SECURITY AND SAFETY (PSS) OF IOT SYSTEMS” Intelligent Management of Industrial IoTBill Karakostas, VLTN CHARIOT-VESSEDIA Workshop 9 May 2019, Dublin, Ireland CHARIOT – VESSEDIA Workshop, 9 May 2019, Dublin, Ireland

2. 01 Topic 1 What is industrial IoT SUMMARY In this talk we focus on the new type of industrial automation that is based on Internet of Things Technologies. We identify the benefits and threats that these technologies present to industrial systems. We then outline an approach to intelligent management of industrial IoT that minimises safety, security, privacy and other enterprise risks. 02 Topic 2 Issues, benefits and risks of Industrial IoT 03 Topic 3 IoT quality 04 Topic 4 AI/ML for IoT risk management CHARIOT – VESSEDIA Workshop, 9 May 2019, Dublin, Ireland

3. What is Industrial IoT (IIoT)? • The term Industrial Internet of Things (IIoT) refers to the use of networked smart sensors and actuators (in other words IoT technologies) to improve manufacturing and industrial processes. • IIoT is closely related to initiatives such as Industry 4.0, that leverages IoT data for real-time analytics on machine generated data in industrial settings. • IIoT can therefore be distinguished from other IoT technologies for domains such as entertainment, personal health care etc. CHARIOT – VESSEDIA Workshop, 9 May 2019, Dublin, Ireland

4. In what ways does Industrial IoT different from other types of IoT? Parameters that differentiate IoT from industrial IoT include but are not limited to: • Security • Interoperability • Scalability • Precision and Accuracy • Programmability • Low latency • Reliability • Resilience • Automation • Serviceability CHARIOT – VESSEDIA Workshop, 9 May 2019, Dublin, Ireland

5. IIoT features • IIoT is essentially the same as traditional IIoT, but possibly hardened (made more robust) to meet the operational/physical conditions of industrial installations. • IIoT is a hardware/software/network based integrated system. • It is produced in several stages of a manufacturing process that includes both hardware and software design and manufacturing. • Its supply chain may be long and complex. • There are no global quality assurance standards for IIoT with the exception of some domains such as healthcare where requirements are more stringent. • For many users of IIoT, the IIoT devices are off-the-shelf ‘black boxes’ for whom there is little visibility/control of the techniques and standards used for their production. CHARIOT – VESSEDIA Workshop, 9 May 2019, Dublin, Ireland

6. Benefits of IIoT for their environment • The main benefit of IIoT is its ability to supply data to the industrial process in real time, that can be used for the efficient/optimal running and control of the process. • One such example involves supplying real-time data about physical systems (machinery) to predict defects before they occur (predictive maintenance). • Another benefit is improved field service. Remote monitoring/diagnosis of equipment installations avoids unnecessary onsite visits by maintenance engineers. • Tracking of industrial assets. The location, status and condition of mobile machinery can be obtained through IIoT. • Facilities management. IioT sensors can capture and transmit monitor vibrations, temperature and other factors in a building and identify problem areas. CHARIOT – VESSEDIA Workshop, 9 May 2019, Dublin, Ireland

7. Risks of IIoT for their environment • However, IIoT can also introduce risks to the industrial environment. Such risks can be context independent, i.e. caused by defects, flaws/errors in the manufacturing process and in the software process that develops and installs software in the IIoT device, along the software supply chain. Other risks are context dependent and depend on how IIoT is deployed, where interactions with other systems (including other IIoT installations) can cause unintended consequences. Finally, there are risks related to intended intervention to the IIoT devices or IIoT network with malicious purposes (‘hacking’). • Overall, the risks can be classified according to the following areas: • Security risks: IIoT can compromise the integrity of industrial assets both physical and digital (i.e. data) • Safety risks: IIoT can (through defects, malfunctioning or other intended or unintended actions or contextual circumstances) can cause industrial processes to enter unsafe states, presenting a risk to assets or humans. • Privacy risks. IIoT, intendedly or un- intendedly compromises the privacy of data that it handles/transmits. CHARIOT – VESSEDIA Workshop, 9 May 2019, Dublin, Ireland

8. IIoT Software Quality Assurance How the different types of IIoT software have been produced should be of importance to the IIoT user, i.e.: • Software Quality Assurance. Has the IoT software (application, system, firmware,..) been designed, developed, integrated, tested by following acceptable QA methods? Does the supply chain of the IoT follow a strict QA regarding modifications, adaptations, new version releases, etc? • Hardware-Software compatibility validation Does the IoT software (at firmware, system, application levels) operate as intended on the IoT hardware within a real IoT environment? • Cross-domain Interoperability testing Is the IoT interoperable with each other and with the host environment (network, gateway, Fog,…) in terms of communication protocols, data formats, encryption standards, etc? • Security Quality Assurance. Does the industrial IoT preserve the integrity of the data in terms of security(unauthorised access). This QA requirement is closely related to the subject industrial domain (e.g. mission, health and safety critical,…) • Acceptance Testing in the targeted industrial, i.e. validating the correct operation of IoT in the real industrial environment, where in contrast to the isolated/limited testing environment/lab of production, is dynamic and introduces new unforeseen conditions and therefore risks. CHARIOT – VESSEDIA Workshop, 9 May 2019, Dublin, Ireland

9. ML Approach to IoT Risk management(1) Main Problem: Given that complete control of IIoT sensors and installations may be impossible (or cost-prohibitively), how can the enterprise reduce the IIoT induced risks to manageable levels? Solution: Apply analytics/machine learning to the sensor data, not only for operational performance purposes, but also for better managing the IIoT installation itself. Benefits: Many costly (manual) processes for sensor and IIoT network maintenance become automated. The system becomes better in managing the IIoT installation over time, as it learns sensor patterns and behaviors using machine learning/analytics on sensor data and metadata. CHARIOT – VESSEDIA Workshop, 9 May 2019, Dublin, Ireland

10. ML Approach to IoT Risk Management (II) Some examples of ML/analytics to improve sensor management: • Time series analysis/mining of sensor data. This can be used to detect anomalies in transmitted sensor data, indicating possible malfunctioning of the sensor, or disturbances in its environment (malicious or unintended). • Detected abnormal topologies in sensor installations. Deviations from the planned installation topology for sensors are detected. An unauthorised sensor installation is detected by the system that can have potential security or privacy risk. • Learning sensor maintenance/update patterns from maintenance logs. As the sensor management system learns maintenance (e.g. software update) patterns, it can detect out of order action (such as firmware update), generating a security alert. CHARIOT – VESSEDIA Workshop, 9 May 2019, Dublin, Ireland

11. CHARIOT Approach to IIoT Management CHARIOT – VESSEDIA Workshop, 9 May 2019, Dublin, Ireland

12. Highlights of the CHARIOT Approach to IIoT Risk Management • IIoT is not directly connected to the industrial system. The CHARIOT Platform acts as an intermediary- a managed environment for industrial IoT installations. • Rigorous mechanisms for ensuring the authenticity of the sensors and the validity of the firmware they run (PKI, blockchain,…) • South and North-bound gateways further filter out ‘bad’ sensors and data and protect the industrial environment. • Dedicated ‘Engines’ for Security, Safety and Privacy apply risk management rules to the sensor data and metadata, ensuring that enterprise policies for safety/security/privacy are adhered to • All process takes place in real time, with low latency (in a ‘Fog’ network), ensuring that invalid sensor data are filtered out before they have the chance to enter the Industrial System. CHARIOT – VESSEDIA Workshop, 9 May 2019, Dublin, Ireland

13. Summary, conclusions and further research directions • Industrial IIoT has great potential to make industrial processes more streamlined, efficient and also safe and secure. • However, IIoT can also bring unintended consequences to the Industrial System, in terms of risks. • Such risks cannot be totally eliminated, they can however be contained within acceptable levels. • Some risks can be reduced with more rigorous processes for IIoT software development, integration and testing, and with better control of the IIoT software supply chain. • Other types of risks must be dealt with in the actual operating environment, as such risks cannot be foreseen or quantified in the production/lab testing environment. • The process of managing IIoT can become more efficient with environments such as the CHARIOT Platform and with similar analytics/ML techniques used currently to process IIoT data. CHARIOT – VESSEDIA Workshop, 9 May 2019, Dublin, Ireland

14. For further questions VLTN BBVA Bill Karakostas billkarakostas@vltn.be The projects CHARIOT & VESSEDIA have received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 780075 & No 731453. CHARIOT – VESSEDIA Workshop, 9 May 2019, Dublin, Ireland