Projects

All projects Privacy Protection & CryptographyBlockchains & Smart ContractsSoftware VerificationDevice & System SecurityMachine LearningFinanceHealthGovernment & HumanitarianCritical InfrastructureDigital Information
Jan 2022 → Dec 2023 Project
Ongoing

PAIDIT: Private Anonymous Identity for Digital Transfers

Partner: ICRC, funded by HAC
Partner contact: TBD
EPFL laboratory: Decentralized Distributed Systems Laboratory (DEDIS)
EPFL contact: Prof. Bryan Ford

To serve the 80 million forcibly-displaced people around the globe, direct cash assistance is gaining acceptance. ICRC’s beneficiaries often do not have, or do not want, the ATM cards or mobile wallets normally used to spend or withdraw cash digitally, because issuers would subject them to privacy-invasive identity verification and potential screening against sanctions and counterterrorism watchlists. On top of that, existing solutions increase the risk of data leaks or surveillance induced by the many third parties having access to the data generated in the transactions. The proposed research focuses on the identity, account, and wallet management challenges in the design of a humanitarian cryptocurrency or token intended to address the above problems.

TopicsPrivacy Protection & CryptographyBlockchains & Smart ContractsDevice & System SecurityFinanceGovernment & Humanitarian

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May 2021 → May 2023 Project
Ongoing

Harmful Information Against Humanitarian Organizations

Partner: ICRC, funded by HAC
Partner contact: Fabrice Lauper
EPFL laboratory: Distributed Information Systems Laboratory (LSIR)
EPFL contact: Prof. Karl Aberer, Rebekah Overdorf

In this project, we are working with the ICRC to develop technical methods to combat social media-based attacks against humanitarian organizations. We are uncovering how the phenomenon of weaponizing information impacts humanitarian organizations and developing methods to detect and prevent such attacks, primarily via natural language processing and machine learning methods.

TopicsMachine LearningGovernment & Humanitarian

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Apr 2021 → Mar 2022 Project
Ongoing

Adversarial Attacks in Natural Language Processing Systems

Partner: Cyber-Defence Campus (armasuisse)
Partner contact: Ljiljana Dolamic
EPFL laboratory: Signal Processing Laboratory (LTS4)
EPFL contact: Prof. Pascal Frossard, Sahar Sadrizadeh

Recently, deep neural networks have been applied in many different domains due to their significant performance. However, it has been shown that these models are highly vulnerable to adversarial examples. Adversarial examples are slightly different from the original input but can mislead the target model to generate wrong outputs. Various methods have been proposed to craft these examples in image data. However, these methods are not readily applicable to Natural Language Processing (NLP). In this project, we aim to propose methods to generate adversarial examples for NLP models such as neural machine translation models in different languages. Moreover, through adversarial attacks, we mean to analyze the vulnerability and interpretability of these models.

TopicsDevice & System SecurityMachine LearningGovernment & Humanitarian

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Feb 2021 → Feb 2023 Project
Ongoing

PriBAD: Private Biometrics for Aid Distribution

Partner: ICRC, funded by HAC
Partner contact: Vincent Graf
EPFL laboratory: Security and Privacy Engineering Laboratory (SPRING)
EPFL contact: Prof. Carmela Troncoso, Wouter Lueks

In this project, we work on providing a privacy-preserving biometric solution for humanitarian aid distribution. The project seeks to understand the requirements of aid distribution in emergency situation and design a solution that enables the use of biometrics without endangering the beneficiaries that need access to aid.

TopicsPrivacy Protection & CryptographyGovernment & Humanitarian

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Jan 2021 → Dec 2022 Project
Ongoing

What If....? Pandemic Policy Decision Support System

Partner: Swiss RE
Partner contact: Mary-Anne Hartley
EPFL laboratory: Machine Learning and Optimization Laboratory (MLO), intelligent Global Health Research group
EPFL contact: Mary-Anne Hartley, Prof. Martin Jaggi, Prakhar Gupta, Giorgio Mannarini, Francesco Posa

After 18 months of responding to the COVID-19 pandemic, there is still no agreement on the optimal combination of mitigation strategies. The efficacy and collateral damage of pandemic policies are dependent on constantly evolving viral epidemiology as well as the volatile distribution of socioeconomic and cultural factors. This study proposes a data-driven approach to quantify the efficacy of the type, duration, and stringency of COVID-19 mitigation policies in terms of transmission control and economic loss, personalised to individual countries.

TopicsMachine LearningHealthGovernment & Humanitarian

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