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11TH FSR ANNUAL CONFERENCE | FROM DATA SPACES TO DATA GOVERNANCE

The 11th FSR Annual Conference is an occasion to take stock of the progress made on the objectives outlined in the EU Data Strategy the Data Governance Act in the network industries. This new regulation will have impact on the various network industries, and at our conference, we will particularly focus on the areas of energy, climate, transport and telecommunications.

Technology Monitoring and Management (TMM)

The objective of the TMM project is to identify, at an early stage, the risks associated with new technologies and develop solutions to ward off such threats. It also aims to assess existing products and applications to pinpoint vulnerabilities. In that process, artificial intelligence and machine learning will play an important part. The main goal of this project is to automatically identify technology offerings of Swiss companies especially in the cyber security domain. This also includes identifying key stakeholders in these companies, possible patents, published scientific papers.

Shoup on Proof of History

For a long time I tried to understand what Proof-of-History brings to the table. What is it useful for? What problem does it solve? At the beginning of may 2022, Victor Shoup, who is a renowned cryptographer and currently working at DFinity, took a deep dive into Proof of History. He wrote an opinion paper on (…)

Campus Lecture with Chelsea Manning

Chelsea E. Manning is a technologist and network security expert whose actions showed the world that the conscience of individuals can make urgent change through bravery and determination. She speaks on the social, technological, and economic ramifications of Artificial Intelligence, and on the practical applications of machine learning. She is a vocal advocate for government transparency and queer and transgender rights as @xychelsea on Twitter and through her op-ed columns for The Guardian and The New York Times.

GymInf – Sécurité et Confidentialité

Course given under the GymInf program of swissuniversities by Linus Gasser.

Subjects for the course:

– why your opinion is worth money
– abusive data collection on personal devices
– protecting internet connections using TLS
– usefulness of blockchains for the decentralization of trust
– homomorphic cryptography for secure data sharing
– legislation on security and privacy in Switzerland, Europe, and elsewhere

Disco

Disco is a framework to implement machine learning algorithms that run in a browser. This allows testing new privacy-preserving decentralized ML algorithms.

Tandem

The Tandem / Monero project is a collaboration with Kudelski. It secures private keys in a privacy-preserving way.

Applied Machine Learning Days – AI & Healthcare

The track “AI & Healthcare” aims at bringing together researchers from academia, public health, start-ups and industry to share experiences and best practices, to jointly discuss the potential of AI in the transformation of healthcare towards a trustworthy system with improved patient and society outcomes.

Applied Machine Learning Days – AI & Cybersecurity

In this track, we explore the role of AI for cybersecurity – its blessing and its curse – and how the private sector, government and academia should collaborate to reduce the threat landscape of AI systems as well as to isolate them with safeguard mechanisms that make it easy to shut down if things start to go wrong.

`derive_builder`: usage and limitations

Basics The builder pattern is a well known coding pattern. It helps with object construction by having a dedicated structure to help build the other. It is usually used when many arguments are required to build one. The example codes are written in Rust, but the concepts behind these can be applied to many languages. (…)

[FR] Chelsea Manning: «J’ai plus d’accès à la guerre en Ukraine avec mon laptop que je n’en avais en Irak»

Dès le lundi 7 mars, Heidi.news invite à prendre de la hauteur par rapport à la guerre en Ukraine et son flot incessant d’informations. Pour cette «semaine des spécialistes», nous sommes partis à la recherche d’esprits aiguisés pour nous aider à mieux comprendre ce qui se joue là, sous nos yeux, à notre porte. Ancienne analyste de l’armée américaine, Chelsea Manning était de passage à l’EPFL pour une conférence co-organisée par la Trust Valley sur le thème du futur des données et de la vie privée en temps de guerre. Heidi.news l’y a rencontrée.

David Atienza elected Chair of the EDAA

Prof. David Atienza, head of the C4DT affiliated Embedded Systems Laboratory (ESL) at EPFL School of Engineering and new Director of EcoCloud, has been elected as Chair of the European Design and Automation Association (EDAA). The EDAA pursues educational, scientific and technical activities for the advancement in the international community of electronic design and design automation.

Privacy-Enhancing Technology Summit Europe 2022

Privacy, security, and regulatory constraints create difficulties for data-driven projects. This includes initiatives involving sensitive data being processed, accessed, monetised, bought, sold, shared, aggregated, or analysed. To unleash the power of sensitive data for these functions, Privacy-Enhancing Technologies (PETs) are being deployed by many different sectors. Industries benefiting range from financial services to healthcare to pharmaceuticals to (…)

Tyche: Confidential Computing on Yesterday’s Hardware

Confidential computing is an increasingly popular means to wider Cloud adoption. By offering confidential virtual machines and enclaves, Cloud service providers now host organizations, such as banks and hospitals, that abide by stringent legal requirement with regards to their client’s data confidentiality. Unfortunately, confidential computing solutions depend on bleeding-edge emerging hardware that (1) takes long to roll out at the Cloud scale and (2) as a recent technology, it is bound to frequent changes and potential security vulnerabilities. This proposal leverage existing commodity hardware combined with new programming language and formal method techniques and identify how to provide similar or even more elaborate confidentiality and integrity guarantees than the existing confidential hardware.

Invariant Federated Learning: Decentralized Training of Robust Privacy-Preserving Models

As machine learning (ML) models are becoming more complex, there has been a growing interest in making use of decentrally generated data (e.g., from smartphones) and in pooling data from many actors. At the same time, however, privacy concerns about organizations collecting data have risen. As an additional challenge, decentrally generated data is often highly heterogeneous, thus breaking assumptions needed by standard ML models. Here, we propose to “kill two birds with one stone” by developing Invariant Federated Learning, a framework for training ML models without directly collecting data, while not only being robust to, but even benefiting from, heterogeneous data.

[FR] Data et IA : comment les entreprises peuvent-elles générer plus de confiance pour leurs clients et utilisateurs ?

Olivier Crochat dirige le Center for Digital Trust, au sein de l’école polytechnique fédérale de Lausanne. Il revient sur le concept de confiance appliquée au monde digital avec un tour d’horizon des questions qui se posent aujourd’hui aux entreprises qui développent des services numériques basés sur la data et l’IA.

Swisscom Joins Nym Privacy Blockchain

Swisscom is joining the Nym network as a validator node. Nym is building the next generation of privacy infrastructure aiming to bring data privacy to all internet users. In doing so, Nym is leveraging blockchain technology to reward nodes that run the global privacy network.

Cyber-Defence Fellowships – A Talent Program for Cyber-Defence Research in Switzerland

To promote research and education in cyber-defence, the EPFL and the Cyber-Defence (CYD) Campus have jointly launched the “CYD Fellowships – A Talent Program for Cyber-Defence Research.”
The fifth call for applications is now open with a rolling call for Master Thesis Fellowship applications, and with a deadline of 14 February 2022 (17:00 CEST) for Doctoral and Distinguished Postdoctoral Fellowship applications. Both new applications and resubmissions are strongly encouraged.

hyperfine, benchmarks for CLIs

Some years ago, I was thinking that by directly look at code difference, I could estimate how faster it would run. I would reflect about complexity or how a given loop will be waay faster by precomputing some values. And of course, it is never that simple. Cache locality, threads synchronization and lock contention are (…)