We want to understand whether analytics and data science can be used to help prevent cyber incidents in our working environments. How can we use big data and data analytics to help us predict cyber attacks and thereby target defence activities to reduce security risks?
We're looking for a team of data experts who can work with us to develop a model which uses patterns, relationships and data to identify cyber security threats. If we know the risks we can take action to prevent incidents more effectively.
EDF Energy is the UK entity of EDF Group and consists of several Business Units with activities ranging from Power Generation (through Nuclear, Coal and Gas stations) to Metering and Customer facing Contact Centres.
Incident reports at EDF Energy are categorised into 3 levels, “Incidents (I)”, “Serious Incidents (SI)” and “Very Serious Incidents (VSI)”. This project is aimed at identifying the key casual factors of SIs.
We would like to understand both internal data sets and external data sets such as external news feeds reporting on security alerts, to find any major gaps in our data tracking that could help us better predict cyber alerts.
- The winner from the pitch day will win up to £20,000 contract to develop a proof of concept for a predictive data analytics solution for EDF Energy. The contract awarded will require the winners to come and work for a few days at our offices.
- If EDF Energy is happy with the work from the proof of concept contract, then a potentially much larger contract to further develop, implement and rollout a fully integrated solution may be awarded in the future (subject to standard procurement processes).
- The winner will also be fast tracked into the last stages of the international EDF Pulse Awards in 2018 where the prize includes €100,000 (subject to a relevant category being available).