Big Data and Security

 

URL has a proven track on research and technology transfer action about “Data & Security”. The focus on this domain is related to the importance that it is acquiring in Industry 4.0. 

Indeed, the vast amount of data generated daily across society and companies is the trigger for the Industry 4.0 revolution. In this context, the ability to manage and exploit the information generated from data fosters both improvement and innovation.

However, all this data and the interconnected systems of the Industry 4.0 should be carefully protected. The threat of cyberattacks is worrying many different critical infrastructure environments such as Smart Grids, finance, public health, transportation systems, alarm and security services, Smart Cities and Industry 4.0 services in general.

For these reasons, Industry 4.0 creates specific challenges to be faced to satisfy the companies’ need to connect heterogeneous technologies operating on the plant floor to a network that can monitor, measure, store, and retrieve data. This allows to automate the industry processes and make it more efficient and effective despite the heterogeneous, distributed and interconnected nature of Industry 4.0, but at the same time it will increase data vulnerabilities to be managed. These are the main aspects that IO4 addresses with the aim to create new operators and managers able to deal with them.

Download here the calendar of the course: Big Data & Security Agenda

 

Contents

Management Systems

Big Data

Cybersecurity

Challenge

After the execution of training courses students have been challenged to push their skills a step forward by working on a prEtotypes for an additional month. The work has been done in group with the support of the University.

The topic of the Challenge for the course “Production Automation System” is presented by the company OHS.

Challenge OHS

PrEtotypes

According to the challenge specifications the students worked on developing a PrEtopype. The PrEtotype has been developed in one month in order to solve the challenge proposed by the company during the course.

Big Data & Security: PrEtotypes

Project Report: Proof of Concept

This document is the final report of the activities conducted by the students within the company during their mobility. It is the result of the work done also by the Coaching Methodologies. 

During the mobility the  company and the students shared practice and technical aspects that gave as result a Proof of Concept.

Project Report: Proof of Concept

Summary of the Project and Mobility

The Sprint4.0 program has meant a rewarding experience for me. It has been a cordial approach to an industry completely different from the one that had worked so far. However, in my previous training in the master I have obtained knowledge and practices that have given me the experience to be able to obtain fair results considering the time with which it was counted.

In general, I can affirm during the process I have had the support of those in charge and those involved in the program. Both during the stay in Germany with the staff of the OHS company we have had a cordial professional approach and in the previous preparation in Spain the coordinator has proven to be decisive and supportive.

In technical terms, before traveling to Germany I have made the document with the proposal of what I could offer the company. Personally, I feel very satisfied because although I did not know in detail the operations of the company, I was able to develop a realistic document that could be followed at least as long as possible. Although some tasks were required, at least 80% of the work was achieved.

It is well known that the job of migrating from files to a database means that the one that most of the time has to be used to process and clean the data. It is laborious but it is necessary to have a robust and uniform database in terms of data types. It is a work that is invested at the beginning of the process, but the results are reflected in that the information can be handled by various tools in both database managers and Business Intelligence tools.

The above mentioned has been a challenge because I personally expected to have more information work. Naturally, that the information was treated has meant spending more time on this and leaving other tasks pending. However, for me it has meant a perfect occasion to use my knowledge regarding the treatment and cleaning of data using the Python programming language and its libraries for data science such as Pandas and NumPy.

A very positive point to note is that for a long time I had the interest to know the PostgreSQL database manager and this has been a good opportunity as it was a requirement for the company. I have learned basic aspects of this tool. In addition to be a practical example, I found myself in situations to be resolved that occur only in cases of real implementation and not in classroom practices.

Finally, the initial desire was that by having the information in an implemented database, as personal advice, a Business Intelligence tool such as tableau or Qlik Sense will be used. Although it has been possible to make the connection pitifully the time has been insufficient to develop the dishoards and everything concerning the visualization of the information that the company has so far.

As a final comment I should mention that although good progress was achieved, perhaps with two or a week more the results would have been more concrete reaching the culmination of the proof of concept.