LAttigo: A lattice-based cryptographic library in Go
The Lattigo library unleashes the potential of lattice-based cryptography in secure multiparty computation for modern software stacks.
Lattigo is a Go package implementing lattice-based cryptographic primitives. The library features:
- A pure Go implementation bringing code-simplicity and easy builds.
- A public interface for an efficient multi-precision polynomial arithmetic layer.
- Comparable performance to state-of-the-art C++ libraries.
Lattigo aims at enabling fast prototyping of secure-multiparty computation solutions based on distributed homomorphic crypto-systems, by harnessing Go’s natural concurrency model.
DPPH: Data Protection for Personalized Health
DPPH seeks to address the main scalability, privacy, security and ethical challenges of data sharing for enabling effective P4 (Predictive, Preventive, Personalized and Participatory) medicine, by defining an optimal balance between usability, scalability and data protection, and deploying an appropriate set of computing tools to make it happen. The target result of the project will be a platform composed of software packages that seamlessly enable clinical and genomic data sharing and exploitation across a federation of medical institutions, hospitals and research laboratories across Switzerland in a scalable, secure, responsible and privacy-conscious way, and that can seamlessly integrate widespread cohort exploration tools (e.g., i2b2, TranSMART or SHRINE).
MedCo: Enabling the Secure and Privacy-Preserving Exploration of Distributed Clinical and Omics Cohorts
MedCo (Medical Cothority) is the first operational system that makes sensitive medical-data available for research in a simple, privacy-conscious and secure way. It enables hundreds of clinical sites to collectively protect their data and to securely share them with investigators, without single points of failure. MedCo applies advanced privacy-enhancing techniques, such as collective homomorphic encryption, secure distributed protocols, blockchains and differential privacy.
SecureKG: Security and Privacy of the Data Science Knowledge Graph
The objective of this project is to enhance the functionalities of the Swiss Data Science Center (SDSC) infrastructure by exploring and laying out the foundations to address the security and privacy requirements stemming from a) the distributed and multi-dimensional architecture of Renga’s knowledge graph, and b) compliance with the new and upcoming data protection regulations for domains dealing with sensitive data. The SecureKG project is carried out in collaboration with SDSC and the DEDIS lab.
PriFi: A Low-Latency, Tracking-Resistant Protocol for Local-Area Anonymity
PriFi is an anonymous communication network for organizations, with low-latency and traffic-analysis resistance. It provably protects members of an organizational network from eavesdropping and traffic-analysis attacks by malicious or coerced insiders, hackers, and malware. PriFi works as a VPN tunnel between the members and a local untrusted server, and supports most protocols (e.g., web-browsing, VoIP, video streaming).
In this project we expose situations where individual privacy can be affected in unforeseen ways, typically due to data interdependencies, we quantify users’ privacy loss in such situations, and we propose technical solutions to keep users informed and to mitigate the privacy risks introduced by others.
Prior Research Activities, 2001 – 2018 (these projects have been phased out)
GameSec: Privacy and Security Games
In this project we have applied game theory in order to analyze several privacy and security problems in the context of location privacy, online advertising, user management in ephemeral networks and individual’s decision about how to manage and secure their genomic data.
AdFraud: Privacy and Security of Online Advertising
The aim of this project was to evaluate the threats to online advertising systems, identify vulnerabilities and exploits of the system, propose countermeasures and evaluate economic incentives of the stakeholders to deploy secure solutions.
SND: Secure Neighborhood Discovery
This project aimed at exploring the security of neighborhood discovery on various levels: from formal reasoning about cryptographic neighborhood discovery protocols, to attacks on the physical communication layer.
SIVC: Secure Inter-Vehicle Communications
This project investigated the different security aspects of vehicular networks, including: threat model, authentication and key management, privacy, as well as secure positioning.
WinetCoop: Cooperation in Wireless Networks
The project studied several issues in selfish wireless networking covering several network types such as 802.11 (Wi-Fi), sensor, and ad-hoc networks.
KeyMan: Key Establishment and Management in Decentralized Wireless Networks
The KeyMan project presented solutions that were specifically targeted at issues of key establishment and key management in decentralized wireless networks, where users have no access to a central authority.
SenseMob: Wireless Sensor Networks with Mobile Elements
This project researched problems around wireless sensor networks with mobile elements, such as, joint sink mobility for lifetime elongation or positioning sensor nodes with mobility differentiated time of arrival.
GComm: Group Communication in Ad Hoc Networks
Group communication service in ad hoc networks is very challenging, due to highly dynamic and unpredictable topological changes. In this project, we studied large scale networks where group communications were used for disseminating crucial information (e.g., cryptographic keys) and small networks where group communications were the dominant communication paradigm.
trans: Traffic and Network Simulation Environment
TraNS (Traffic and Network Simulation Environment) is a GUI tool that integrates traffic and network simulators (SUMO and ns2) to generate realistic simulations of Vehicular Ad hoc NETworks (VANETs). TraNS allows the information exchanged in a VANET to influence the vehicle behavior in the mobility model. For example, when a vehicle broadcasts information reporting an accident, some of the neighboring vehicles may slow down.