|Project Number||Proposal Acronym||Lead Partner (name)||Partners||Keywords||Abstract|
Better Internet Search Ltd, UK
Project lead: Gordon Povey
|Edinburgh Napier University||browsing, user-centric, machine-learning, privacy|
There has been growing dissatisfaction with incumbent search engines and their use of our personal data for targeting advertising. An alternative user-focused business model will be tested with real users during this project to prove not only the technical viability but also the commercial viability of the new user-focused models.
This project will deliver a demonstrator to show that internet search can be significantly improved by adopting a user-focused model for both the ranking of results and for the monetisation of the search engine itself. The project team has already developed an ad-free organic search engine and in this project supervised machine-learning is applied to improve the ranking and personalisation of results while fully respecting the privacy of the user by keeping all personal data on the user-side and under the control of the user.
Danube Tech GmbH, Austria
Project lead: Markus Sabadello and Dominik Beron
|SSI, open-source, user-control, decentralise, messaging app|
A small number of organizations manage most online interactions/communication leading to known centralization issues (e.g. data silos, privacy scandals, massive security breaches). Also, online fraud (e.g.ID theft caused by phishing) is creating billions in damages. Solution (Project): To create a human-centric internet we need to decentralize the way people interact online and give them control over their data and digital identities. To realize this, the project will develop "Context", a novel type of application that is decentralized on all architectural layers and can utilize SSI, i.e. an open, universal and extensible identity infrastructure.
Virtual Angle BV, Netherlands
Project lead: Pedro Branco
|user-control, portal, big data|
In 2011 the World Economic Forum(WEF) issued a report stating that 15 billion devices will be connected to the internet by 2015 and 50bn by 2020. The amount of data stored on the internet is predicted to grow exponentially and looks set to be 44 times larger in 2020 than it was in 2009. Global internet services revenue has also grown strongly over the last ten years, and is forecasted to reach 554 billion Euros in 2019.
Internet giants have business models underlined by the use of personal data, but most people would have trouble knowing who exactly has access to their personal data, for what it is being used for and what benefits it’s generating for the enterprises that are using it. Artificial Intelligence and Big Data technologies potentiate an increasing number of personal data applications. Advertisement, Medical, Banking and Media industries are profiting while using individual’s personal data while not delivering adequate compensation to each individual.It’s urgent to increase transparency regarding the usage of personnel data by enterprises and to ensure that users are better compensated for providing others with access to their personal data.
INSTANT aims to empower users with a transparent tool to manage the access to their personal data and to support due compensation by its use by third parties.INSTANT is focused in delivering a common interface where users will be able to: store the information of each organisation to whom they delivered personal information; create, edit and revoke personal data access given to each specific organisation; manage potential financial compensations given by each organisation for using the user’s personal data. INSTANT will deliver an online portal, and an associated set of web services and protocols, which will serve as interface towards individuals and the data industry.
Diabetes Service ApS, Denmark
Project lead: Jan Leindals
|OwnYourData, Austria||privacy, sensitive data, self-monitoring, open source|
There are 425 million adult people (1 out of 11) diagnosed with Diabetes in the world today and it is a growing epidemic. The diabetes treatment is a very complex puzzle to get the right dose of medicine and many people do not have adequate resources to follow the prescribed dose regimes. This leads to serious healthcare issues and increased costs.
The good news is that technology like self-monitoring devices of blood glucose can help solve the dose puzzle by using a data-driven diabetes management approach. Sharing these new digital health data from self-monitoring devices with doctors, researchers and others is indispensable for success. We believe that our innovation is a paradigm shift in sharing self-monitoring health data. The innovation will be open source, empower the individual by sharing data in a secure, trusted, auditable, traceable and consensus-based way inspired by MyData principles.
MyPCH presents a standardized way to exchange health data in a privacy- respecting data flow between various stakeholders in use cases, so the user can:
Athena Research and Innovation Center in
Project lead: Vassilis Tsaoussidis
|University College London, UK||decentralised, DLT, reputation|
The Internet, initially designed as a distributed system, has become increasingly centralized in recent years and relies on centralized mechanisms to support its core functions, such as trust . At the same time content, although largely created by, and exchanged among users at the edges of the network, is stored on commercial, centralized, services.
This project focuses on assessing the feasibility of deploying a decentralized, reputation -based trust mechanism to solve security and trust problems in Named Data Networking , a future Internet architecture. We consider two use-cases: In the first one, we provide a lightweight mechanism to validate content authenticity in the intermediate routers to mitigate cache poisoning attacks, a serious security threat in NDN. In the second one, we consider trust ratings to be tied to content quality, assessing the feasibility of deploying such a mechanism at the network layer to prevent malevolent content (e.g. fake news) from spreading in the network.
To decentralize our trust scheme and eliminate single-point s of failure, TCN will leverage the blockchain paradigm. Furthermore, we utilize the Proof-of-Prestige consensus algorithm to bring our platform closer to real-world deployment, by inducing an incentives and reward s system for users to provide their ratings and assess its effectiveness.
Assured AB, Sweden
Project lead: Joachim Strömbergson
|HSM, cryptography, key management|
Working since 2014 the CrypTech project (https://cryptech.is/) has developed an open-source hardware cryptographic engine design to meet the needs of high assurance Internet infrastructure systems that use cryptography. Our open-source hardware designs are aimed to be of general use to the broad Internet community, covering needs such as securing email, web, DNSSEC, PKIs, etc. The project has produced a design and hardware boards that have been used in various experiments and tests.
The current design has been the subject of a positive external security evaluation (https://cryptech.is/2018/10/external-security-audit-completed/), though of course some possible improvements were identified in that process that are being or have been addressed. NGI-Trust funding will fund the Cryptech core team in designing and prototyping our next revision Cryptech designs/board.
A Community-driven Approach to Privacy Awareness
project lead: Giorgos Flouris
|IN2||consent, privacy, terms of service,|
In an increasingly instrumented and inter-connected digital world, citizens generate vast amounts of data, much of it being valuable and a significant part of it being personal. However, controlling who can collect it, limiting what they can do with it, and determining how best to protect it, remain deeply undecided issues. CAP-A will deploy a socio-technical solution based on collective awareness and informed consent, where by data collection and use by digital products are driven by the expectations and needs of the consumers themselves, through a collaborative participatory process and the configuration of collective privacy norms.
|PANGA, France||MyDataBall, France||IoT, data privacy, big data, consent, SSI|
Since the democratization of Internet, new businesses have been emerging, leading to the explosion of e-commerce market places and the IoT which is providing many connected devices and solutions for all business sectors(healthcare, automatic domestic equipment, automotive industry, etc.). Data privacy is thus becoming more and more challenging as people are giving their personal data to big companies (likeGAFAMI), inadvertently, or without being quickly and visually aware of the risks, or just because of lack of protection solutions.
The PY box is the central check point for all your connected devices. This complete hardware and software solution aim at informing and protecting citizens from the unknown connections and unwanted data flows that automatically start when a device is connected to internet. Thanks to a user-friendly interface, the system graphically shows the status of all the activities, provides risks assessment and allows you to define your personal security settings and your authorized personal data.
PY platforms will protect you without fear of degrading the functionality of your devices. On the contrary, the speed of use will be improved by reducing unnecessary connections or messages. The AI module will serve your interests while preserving you from the undesirable. Addressed challenges:The digital identity protection, through the creation of dynamic and volatile digital avatars thanks to SSO systems in order to avoid the calculation of metadata, the trace ability of the activity, the use of uniqueID and password for several websites. The protection of local network, by implementing solutions that are developed on purpose: Firewall, IPS and anti-virus that are integrated on a unique platform. The growth of awareness of risks related to IoT, PC and smartphone data, by warning the users about the possible threats and by performing risks analysis that can be viewed on a user-friendly interface.
Educate, Understand: Act, Control, Trust & Value your Data when going online.
A dynamic VPN by design (as an API) & a Personal Data Passport including Portrait-Right; For All!
Project lead: Laurent Engel
NHL Stenden University of Applied Science
|DLT, app, privacy, user centric|
Imagine a world where all individuals have control over their personal data. No data lost or stolen, full control and ownership in the online spectrum. That’s a friendly & trustworthy system. ValueMe is creating this ecosystem. A C2B principle, individuals in control, aiming at safer, relevant and more trustable online journeys & relationships.
ValueMe noticed; “current online activities are poisoned by advertising models creating waste, irrelevance, less trust”.
Context-aware Privacy Protection for Mobile Devices
|Joao P. Vilela, Portugal||Alastair Beresford, UK||privacy, mobile, user centric||The main goal of the COP-MODE project is to advance the state-of-the art on privacy protection mechanisms for mobile devices operating in ubiquitous computing environments. The pervasiveness of mobile devices (e.g. smartphones) allows great quantities of data to be collected at all times. This collection can be beneficial for both users and collecting entities, by facilitating user-tailored services. However, much of this data can also be considered private and sensitive, thus requiring privacy protection mechanisms that can provide an adequate trade-off between utility and privacy. Current systems fail to provide adequate privacy protection by relying on an ask-once use-every-time approach, in which mobile applications ask for access to certain types of information at install, and have access to that information at all times without user intervention. Warning users of privacy risks has proven ineffective due to warning fatigue, in which users gradually dismiss messages that become annoying or intrusive, especially when users have dozens of applications, each with several privacy-related preferences to set. Moreover, some studies have shown that there is an inherent context-dependence of privacy decisions; however context is challenging to model and define. In this project we plan to address some of these challenges, in particular we plan to gather the necessary data for developing privacy profiles that map privacy preferences with context. These datasets and privacy profiles shall form the basis for future development of automated mechanisms for setting privacy preferences on behalf of users according to current context.|
Decentralised Edge Gateways for Trusted In-Network Computing
Fluentic Networks Ltd, UK
Project lead: Dirk Kutscher
|cloud, IoT, decentralised, network stack, DLT|
The traditional, centralized cloud computing model in use today has difficulty handling new and emerging applications and networking paradigms. As user and IoT devices are becoming ever more powerful, they are producing enormous amounts of data, for safety (street cameras), entertainment (UGC and AR/VR applications), health monitoring (wearable devices) and intelligent transport applications (autonomous vehicles).
Pulling this data into the cloud for processing is impossible due to the enormous volume, but also due to stringent latency requirements. Instead, in-network and edge-network devices will collectively form edge computing swarms and complement the cloud with their data storage and processing resources. This shift from centralized to in-network compute has the potential to open up new horizons for application development, ultimately, creating new markets for storage and processing resources.
DECentralized Identity and User Experience
University of Stuttgart (USTUTT), Germany
|decentralised, SSI, DLT, privacy|
Decentralized identities (DIDs), also referred to as Self Sovereign Identities (SSI), are a novel promising approach to Identity Management (IdM) based on the Blockchain technology and a Privacy Enhancing Technology (PET). Numerous companies and projects whether big or small, are currently working to make this approach a product for trustworthy and privacy friendly identification in digital interactions. Their technical architecture and proofs of concept show that it is possible to realize such Blockchain- based IdM solutions. This promises to lead the way for a new area of PETs , which would lead to a trustworthy and privacy-friendly internet. However, experience shows that although PETs are a major building block for ensuring privacy on the internet and even though they have a high technical functionality and security, user adoption and diffusion of secure and privacy friendly IdM and similar technologies are not as high as they could be.
Currently, development of PETs focuses mainly on the technical feasibility and implementation. Usability for end users and service providers’ requirements are often neglected. Thus, the technology is often very secure and privacy friendly but lacks applicability in practice. This leads to users not adopting PETs as well as they could be, resulting in security or privacy inci- dents. Moreover, the (business) potential of PETs is not fully exploited, as they are not attractive enough to service providers and therefore rarely integrated into services.
Design 4 Security - Making VPNs Easy
|VPN, privacy, identity, user friendly|
Let’s Connect! provides an open source secure VPN solution allowing ISPs, hosters and businesses to easily setup a secure VPN service. After deployment, users have a safe path either to their company or to the Internet from all generic devices. What makes Let’s Connect! unique in respect to other VPN solutions? Let’s Connect! is the only Open Source solution that has released both server-side management software as all clients apps. The other key strengths of Let’s Connect! come from the focus on security and strong cryptography; the integration with existing Identity Management Systems ; the focus on privacy and GDPR compliance. The project is known under two names: Let's Connect! and eduVPN. The brand eduVPN is used to promote this VPN solution to international educational and research organizations. Let’s Connect! has been supported by GÉANT project, RIPE community fund, SIDN fund (.nl registry), Vietsch Foundation and the NREN community.
Twitter : https://twitter.com/CASPER_NGITRUST
School of Electrical Engineering (ETF), Serbia
O Mundo da Carolina - Associação de Apoio Crianças e Jovens
Faculty of Computer Science and Engineering, "Ss. Cyril and Methodius" University, Skopje (KINKI)
|sensitive data, privacy, protection, AI|
As children are a particularly sensitive category, next generation Internet should be designed in such a way to protect them from both general (untargeted) threats and threats based on user profiling. Current way of user profiling and data collection strategies are particularly dangerous for them - as even adult individuals need help to make more informed decisions on the relevance of information that they are asked to disclose when accessing and using services.
CCS Cozy Cloud's Shiffremir
Cozy Cloud, France
|privacy, personal data, encryption, user control|
Today’s internet most successful platforms (Google, Facebook, etc.) not only neglect users’ privacy but base their business model on personal data brokering. Indeed, over the past decade, personal data has become the new gold across all sectors. At the same time, repeated scandals resulting from personal data leaks led to awareness raising over the past years1,2. Furthermore, in Europe, the GDPR now protects users against data misuse. Consequently, privacy has become both one of the main challenges and an extremely valuable criterion of the next generation internet services.
Cozy is a French start-up that has developed an open-source cloud platform protecting your personal data. Our ambition is to reverse the established order to empower internet users as we provide them their own “digital home” and give them back the control of their data. We already dedicated over 6 years of research to our project and want to go further to fulfil our initial goal and commitments. As one of the most powerful leverage for a real privacy enforcement, the Cozy Cloud's Shiffremir (CCS) project focuses on data encryption.
|IoT, licensing, user privacy||One of the main issues related to the upcoming vision of the IoT is related to privacy: in particular, setting privacy controls. Nowadays, we tend to go through software licences without reading them, as they are too complex, too long, and written in legal jargon: usually we get to the end and press “I agree” without reading a single word. With the advent of a large number of connected objects, able to sense our environment, it is of fundamental importance to give to all users means to control the privacy settings. Furthermore, it would be very relevant to propagate them to semantically similar devices. On top of it, several connected objects may not even have displays (or just very basic ones), making this task even more difficult. The objectives of this study are therefore three: on the front side, develop a human-centric interface, providing the best User Experience for managing privacy settings; on the back side, an architecture, including design patterns and interfaces and algorithms to propagate them and transport them between different providers and objects; on the “far away” side, how to make the above-mentioned work meaningful and a long-term success.|
Keyn B.V., Netherlands
|authentication, apps, browser extension, encryption, decentralisation, software dev|
Password authentication has been the primary means of authentication for web applications since the early days of the Internet, but suffers from both security and usability issues. We are developing a solution that allows people to log in to websites more easily and more securely using their smartphone. It bridges the gap from password authentication to strong authentication on the web, by creating a uniform user experience for a variety of existing authentication methods. The solution consists of a smartphone application and browser extension, which communicate over an end-to-end encrypted communication channel. All secrets are stored on the smartphone, and the browser extension is required to send a request to the smartphone if it needs to authenticate. The user authorises these requests by authenticating to the phone.
Deep-Learning Smart-Enhance Mobile Application that Makes Video/Image Enhanced by Processing Data in the Neural Processing Unit While Fully Preserving User Privacy
Dr. Mohammad Hasan Bahari
|image manipulation, personal data, privacy|
There are different image enhancement app (Letsenhance.io and Google DeepAngel) that improve the quality of images or edit them automatically through advanced artificial intelligence. These apps require users to send their images to their cloud to process them. This increases the risk of getting hacked, scandalized or abused and potentially violates the privacy of millions of users. This is all because these apps work based on deep-learning that is computationally heavy and requires strong GPU servers.
SensifAI offers a game-changing technology that solves this problem. SensifAI have developed specific deep learning architectures for the new NPU chipsets of most major smartphone manufacturers. With this technology, the project can enhance users’ images and videos locally on their mobile phone without any connection to the internet.
With this project, Sensifai delivers on-device, smart-enhance app that can help millions of people enhance their video/image archives while guaranteeing control over their personal data. The project will also add automatic and realtime face and vehicle license plate detection/blurring system in future versions of the app such that users can avoid unwanted violation of other peoples privacy in public area while live broadcasting or sharing images/videos in internet.