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The EU H2020 program is continuing its efforts to establish scientific communities in Europe through the SPARTA project dedicated to cybersecurity. This 3-year project will bring together researchers to take up the new cybersecurity challenges: providing defense against new attacks, offering protection in highly-connected computing environments and artificial intelligence security. Hervé Debar, a researcher in cybersecurity at Télécom SudParis participating in SPARTA, explains the content of this European initiative led by the CEA, with the participation of Télécom ParisTech, IMT Atlantique and Mines Saint-Etienne.

What is the goal of SPARTA?

Hervé Debar: The overall goal of SPARTA is to establish a European cybersecurity community. The future European regulation on cybersecurity proposes to found a European center for cybersecurity competencies in charge of coordinating a community of national centers. In the future, this European center will have several responsibilities, including leading the R&D program for the European Commission in the field of cybersecurity.  This will involve defining program objectives, calls for proposals, selecting projects and managing their completion.

What scientific challenges must the SPARTA project take up?

HD: The project encompasses four major research programs. The first, T-SHARK, addresses the issue of detecting and fighting against cyberattacks. The second, CAPE, is aimed at validating security and safety features for objects and services in dynamic environments. The third, HAII-T, offers security solutions for hardware environments. Finally, the fourth, SAFAIR, is aimed at ensuring secure and understandable artificial intelligence.

Four IMT schools are involved in SPARTA: Télécom SudParis, IMT Atlantique, Télécom ParisTech and Mines Saint-Étienne. What are their roles in this project?

HD: The schools will contribute to different aspects of this project. The research will be carried out within the CAPE and HAII-T programs to work on issues related to hardware certification and security, or the security of industrial systems. The schools will also help coordinate the network and develop training programs.

Where did the idea for this project originate?

HD: It all started with the call for proposals by the H2020 program for establishing and operating a pilot cybersecurity competencies network. As soon as the call was launched, the French scientific community came together to prepare and coordinate a response. The major constraints were related to the need to bring together at least 20 partners from at least 9 countries to work on 4 use cases. The project has been established with four national communities: France, Spain, Italy and Germany. It includes a total of 44 partners from 13 countries to work on 4 R&D programs.

Which use cases will you work on?

HD: The project defines several use cases—this was one of the eligibility requirements for the proposal. The first use case is that of connected vehicles, verifying their cybersecurity and operational safety features, which could be integrated into a test vehicle like EuroNCAP. The second use case will look at complex and dynamic software systems to ensure user confidence in complex computer systems and study the impact of rapid development cycles on security and reliability. The intended applications are in the areas of finance and e-government. Other uses cases will be developed over the course of the project.

What will the structure and coordination look like for this SPARTA community?

HD: A network of organizations outside SPARTA partners will be required to coordinate the community. The organizations that have been contacted are interested in the operations and results of the SPARTA project for several reasons. Two types of organizations have been contacted: professional organizations and public institutions. In terms of institutions, French regions, including Ile-de-France and Brittany, are contributing to defining the strategy and co-funding the research. In terms of professional organizations, the ACN (Alliance pour la Confiance Numérique) and competitiveness clusters like Systematic help provide information on the needs of the industrial sector and enrich the project’s activities.

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SPARTA: a diverse community with bold ambitions

The SPARTA consortium, led by the CEA, brings together a balanced group of 44 stakeholders from 14 Member States. In France, this includes ANSSI, IMT, INRIA, Thales and YesWeHack. The consortium is seeking to re-imagine the way cybersecurity research, innovation, and training are performed in the European Union through various fields of study and expertise and scientific foundations and applications in the academic and industrial sectors. By pooling and coordinating these experiences, competencies, capacities and challenges, SPARTA will contribute to ensuring the strategic autonomy of the EU.

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The H2020 ANIMATAS project, launched in January 2018 for a four-year period, seeks to introduce robots with social skills in schools to assist teaching staff. Chloé Clavel, a researcher in affective computing at Télécom ParisTech, one of the project’s academic partners, answered our questions on her research in artificial intelligence for the ANIMATAS project.

What is the overall focus of the European project ANIMATAS?

The ANIMATAS project focuses on an exciting application of research in artificial intelligence related to human-agent interactions: education in schools. The project also contributes to other work and research being carried out to integrate new technologies into new educational methods for schools.

The project’s objectives are focused on research in affective computing and social robotics. More specifically, the project aims to develop computational models to provide the robots and virtual characters with social skills in the context of interactions with children and teachers in the school setting.

What are the main issues you are facing?

We are working on how we can incorporate robots to allow children to learn a variety of skills, such as computational thinking or social skills. The first issue concerns the robot or virtual character’s role in this learning context and in the pre-existing interactions between children and teachers (for example, counselors, colleagues or partners in the context of a game).

Another important issue relates to the capacity of the underlying computational models responsible for the robots’ behavior to adapt to a variety of situations and different children. The objective is for the robot to be attentive to its environment and remain active in its learning while interacting with children.

Finally, there are significant ethical issues involved in the experiments and the development of computational models in accordance with European recommendations. These issues are handled by the ethics committee.

Who else is involved with you in this project, and what are the important types of collaboration in your research?

We have partners from major European academic laboratories. The majority are researchers in the field of affective computing, but also include researchers in educational technologies from the École Polytechnique Fédérale de Lausanne (EPFL), with whom we are working on the previously mentioned issue of the robot’s role in the learning process.

Three researchers from Télécom ParisTech are involved in this project: Giovanna Varni and myself, from the Images, Data and Signal Department and Nicolas Rollet, from the Economic and Social Sciences Department.

ANIMATAS requires skills in computer science, linguistics, cognitive sciences and pedagogy… What areas are the researchers from Télécom ParisTech contributing to?

Télécom ParisTech is contributing skills in affective computing and computational linguistics. More specifically, my PhD student, Tanvi Dinkar, and I are working on the automatic analysis of disfluencies (for example, hesitations, unfinished words or sentences) as a sign of a child’s emotions or stress in the learning process, or their level of confidence in their skills (feeling of knowledge) in the context of their interactions with other children, the teacher or the robot.

How will the results of ANIMATAS be used?

The project is a research training network, and one of its main objectives is to train PhD students (15 for ANIMATAS) in research as well as uniting work around affective computing and social robotics for education.

The project also includes unfunded partners such as companies in the field of robotics and major US laboratories such as ICT (Institute of Creative Technologies) and USC (University of Southern California) who provide us with regular feedback on scientific advances made by ANIMATAS and their industrial potential.

A workshop aimed at promoting ANIMATAS research among industrialists will be organized in September 2020 at Télécom ParisTech.

What is the next step in this project?

The kick-off of the project took place in February 2018. We are currently working with schools and educational partners to define interaction scenarios and learning tasks to collect the data we will use to develop our social interaction models.

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EURECOM is coordinating the three-year European project, PAPAYA, launched on May 1^st. Its mission: enable cloud services to process encrypted or anonymized data without having to access the unencrypted data. Melek Önen, a researcher specialized in applied cryptography, is leading this project. In this interview she provides more details on the objectives of this H2020 project.

What is the objective of the H2020 Papaya project?

Melek Önen: Small and medium-sized companies do not always have the means to internally process large amounts of data that is often personal or confidential. They therefore use cloud services to simplify the task, but in so doing they lose control over their data. Our mission with the PAPAYA project (which stands for PlAtform for PrivAcY-preserving data Analytics) is to succeed in using data processing and classification methods while keeping the data encrypted and/or anonymized. This would offer companies greater security and confidentiality when they use third party cloud services, since these services could no longer access the unencrypted data. This has become a major issue since the European General Data Protection Regulation (GDPR) has come into effect.

What is your main challenge in this project?

MÖ: Today, when we encrypt data the traditional way, it is protected in a randomized manner—in other words, using a method that lacks transparency. It is impossible to carry out operations on data in this state. In 2009, cryptography researcher Craig Gentry proposed a unique method called fully homomorphic encryption. Using this method, several operations can be carried out on encrypted data. The problem is, processing data this way is not very efficient in terms of memory usage and the processes required. The majority of our work will involve designing variants of the data processing algorithms that will be compatible with data protected by homomorphic encryption.

Can you explain how you design variants of data processing algorithms?

MÖ: For example, a neural network contains both linear operations that are easily managed with appropriate encryption methods as well as non-linear operations.  We do not know how to process encrypted data using non-linear operations. Yet the network’s accuracy depends on these non-linear operations, so we cannot do without them. What we must do in this situation is approximate these operations, which are actually functions, by using other linear functions with similar behavior. The more effective this approximation, the more accurate the neural network, and we can therefore process the encrypted data.

What use cases do you plan to work on?

MÖ: We have two different use cases. The first is medical data encryption. This situation affects many hospitals that have patients’ data but are not large enough to have their own internal data processing services. They therefore use cloud services. The second case involves web analytics and it could be useful for the tourism sector. Data collected by smartphone users could be very useful in this sector that analyzes the way tourists move from one place of interest to another. For both cases, we imagine several progressive scenarios. First, for one data owner who has all the users’ unencrypted data that he encrypts with the same key and transfers to the cloud. Next, several owners with several keys. Finally, we consider data that comes directly from users.

Who else is working on this project with you?

MÖ: PAPAYA brings together 6 partners including EURECOM, which is coordinating the action. The companies involved in assisting us with the use cases and in designing this new platform are Atos, IBM, Haifa Research Lab, Orange Labs, and MediaClinics—an SME that makes sensors for monitoring patients in hospitals. In terms of academic partners, we are working with Karlstad University in Sweden. We will work together for the entire three-year project.

Within the framework of the German-French Academy for the Industry of the Future, a partnership between IMT and Technische Universität München (TUM), the HyBlockArch project examines the future of the blockchain. This project aims to adapt this technology to an industrial scale to create a powerful tool for companies. To accomplish this goal, the teams led by Gérard Mémmi (Télécom ParisTech) and Georg Carle (TUM) are working on new blockchain architectures. Gérard Memmi shares his insight.

Why are you looking into new blockchain architectures?

Gérard Mémmi: Current blockchain architectures are limited in terms of performance in the broadest sense: turnaround time, memory, energy… In many cases, this hinders the blockchain from being developed in Industry 4.0. Companies would like to see faster validation times or to be able to put even more information into a blockchain block. A bank that wants to track an account history over several decades will be concerned about the number of blocks in the blockchain and the possible increase in block latency times. Yet today we cannot foresee the behavior of blockchain architectures for many years to come. There is also the energy issue: the need to reduce consumption caused by the proof of work required to enter data into a blockchain, while still ensuring a comparable level of security.  We must keep in mind that the bitcoin’s proof of work consumes the same amount of electrical energy as a country like Venezuela.

What type of architecture are you trying to develop with the HyBlockArch project?

GM: We are working on hybrid architectures. These multi-layer architectures make it possible to reach an industrial scale. We start with a blockchain protocol in which each node of the ledger communicates with a mini data storage network on a higher floor. This is not necessarily a blockchain protocol and it can operate slightly differently while still maintaining similar properties. The structure is transparent for the users; they do not notice a difference. The miners who perform the proof of work required to validate data only see the blockchain aspect. This is an advantage for them, allowing them to work faster without taking the upper layer of the architecture into account.

What would the practical benefits be for a company?

GM: For a company this would mean smart contracts could be created more quickly and the computer operations that rely on this architecture would have shorter latency times, resulting in a broader scope of application. The private blockchain is very useful in the field of logistics. For example, each time a product changes hands, as from the vendor to the carrier, the operation is recorded in the blockchain. A hybrid architecture records this information more quickly and at a lower cost for companies.

This project is being carried out in the framework of the German-French Academy for the Industry of the Future. What is the benefit of this partnership with Technische Universität München (TUM)?

GM: Our German colleagues are developing a platform that measures the performance of the different architectures. We can therefore determine the most optimal architecture in terms of energy savings, fast turnaround and security for typical uses in the industry of the future. We contribute a more theoretical aspect: we analyze the smart contracts to develop more advantageous protocols, and we work with proof of work mechanisms for recording information in the blockchain.

What does this transnational organization represent in the academic field?

GM: This creates a European dynamic in the work on this issue. In March we launched a blockchain alliance between French institutes: BART. By working together with TUM on this topic, we are developing a Franco-German synergy in an area that only a few years ago was only featured as a minor issue at a research conference, as the topic of only one session. The blockchain now has scientific events all to itself. This new discipline is booming and through the HyBlockArch project we are participating in this growth at the European level.