Kategori: Cybersecurity

  • TrustNet Business Network

    TrustNet is an important network initiative to keep pace with- and capitalize on- growth opportunities related to securing technology and critical infrastructure. Whereas the market for frontier technologies (AI, IT, OT) is projected to grow rapidly from $2.5 trillion in 2023 to $16.4 trillion by 2033, and the market for AI assurance is expected to double every year (108% CAGR), TrustNet represents a significant strategic opportunity to differentiate Norwegian companies and technology ecosystems on trust.

    Norway’s private sector and research institutions have the expertise required to ensure digital trust, but digital infrastructure and innovation ecosystems for data sharing and AI are fragmented across sectors and domain silos. Norway could be an ideal innovation testbed for next-generation digital infrastructure, but coordination across public and private sectors with investors and research institutions is needed to enable trust in technology, and with it, capital and procurement channels for growth.

    TrustNet is supported by leading experts and stakeholders in secure IT-OT integration, including SMEs, municipalities, investors, and research partners, notably SFI NORCICS, NESIOT and the European Cluster for Securing Critical Infrastructures (ECSCI). 

    Akershus Fylkeskommune has provided funding to establish TrustNet as a business network, and the TrustNet Secretariat and Board of Advisors are additional grant applications to finance coordination of national and international collaborations in R&D, marketing, investment, and distribution/export of Norwegian technology and expertise over the next 3 years.

    TrustNet’s members are involved in national and international R&D proposals with a total cost budget of about 680 MNOK. An already approved EU innovation project “AI-Cyber” has an estimated cost of €31 million with collaboration partners in 12 countries, and 4 use cases in Seaport Critical OT, Banking, Critical Telecommunications, and Industrial Automation OT. In addition, TrustNet members are developing proposals in Norway for use cases in Healthcare, Finance, Energy, Maritime, and Dual-Use.

    Call to Action, Requirements and Benefits

    • TrustNet is calling on stakeholders, involved with critical infrastructure and digital transformation, to join the initiative and provide non-binding letters of intent (LOI) as an entry ticket to participation in upcoming project proposals, funding applications, access shared infrastructure, pilot demonstrations, networking events, and delegations to promote and export expertise and solutions for secure IT-OT integration.
    • LOIs indicate areas of interest (e.g., provide/receive expertise, tech) and will serve as a basis for planning activities, assembling consortia and task forces where applicable. 
    • TrustNet will provide each partner with an overview of relevant opportunities at least annually. 
    • Indicative partner financing and/or personnel and technology contributions can be applied to receive benefits of at least equivalent value (e.g., access to services, products, financing).

    No obligations or payments are binding until specific activities and benefits are confirmed.

    To express interest in the TrustNet initiative, please contact the TrustNet Secretariat at trustnet@venturenet.no.

    For more information, feel free to contact any TrustNet representative, e.g., Christian Haukaas, Sokratis Katiskas, Habtamu Abie, and Inge Kampenes.

  • Decentralised AI

    Decentralised AI

    (INSIGHTS) (TECHNOLOGY) (PROJECT) Massachusetts Institute of Technology (MIT) Media Lab. “Decentralized AI”. Accessed 24.08.2025. https://www.media.mit.edu/projects/decentralized-ai/overview/

    As AI evolves beyond screen assistants and into dimensional applications, decentralization emerges as the critical factor for unlocking its full potential.

    Introduction

    The AI landscape is at a crossroads. While advances continue, concerns mount about job displacement and data monopolies. Centralized models, dominated by a few large companies, are reaching their limits. To unlock the true power of AI, we need a new paradigm: decentralized AI.

    Challenges of Centralized AI

    • Limited data access: Siloed data restricts AI’s potential for applications like personalized healthcare and innovative supply chains.
    • Inflexible models: One-size-fits-all models struggle with diverse real-world scenarios, leading to inaccurate and unfair outcomes.
    • Lack of transparency and accountability: With data and algorithms hidden away, trust in AI erodes, hindering adoption and innovation.

    Decentralized AI: A Vision for the Future:

    • Data markets: Secure marketplaces enable data exchange while protecting privacy and ensuring fair compensation.
    • Multi-dimensional models: AI that learns from real-world experiences through simulations and agent-based modeling.
    • Verifiable AI: Mechanisms like federated learning and blockchain ensure responsible development and deployment of AI models.
    • Exchanges for AI solutions: Platforms where individuals and businesses can access and contribute to AI solutions for diverse needs.

    Opportunities in Decentralized AI:

    • Democratization of innovation: Individuals and smaller businesses can participate in the AI revolution, creating valuable solutions and capturing economic benefits.
    • Unleashing trillions in economic value: By addressing real-world challenges in healthcare, education, and other sectors, decentralized AI can unlock vast economic opportunities.
    • Building a more equitable and inclusive future: Decentralization empowers individuals and helps address concerns about bias and discrimination in AI.

    The Call to Action:

    In this pivotal moment, everyone has a role to play. Businesses must embrace decentralized models, governments should foster collaborative ecosystems, and individuals must become AI literate and contribute their expertise. By working together, we can unlock the true potential of AI and build a more prosperous and equitable future for all.

    Reach out to us at dec-ai@media.mit.edu

    Professor Ramesh Raskar spoke on this topic at EmTech Digital in May 2024. 

    Research Topics

    #social networks #computer vision #artificial intelligence #data#privacy #machine learning #decision-making

  • Privacy-enhancing technologies

    Privacy-enhancing technologies

    The Royal Society. “Privacy-enhancing technologies.” Accessed 18.08.2025. https://royalsociety.org/news-resources/projects/privacy-enhancing-technologies/.

    What are Privacy Enhancing Technologies (PETs)? 

    Privacy Enhancing Technologies (PETs) are a suite of tools that can help maximise the use of data by reducing risks inherent to data use. Some PETs provide new tools for anonymisation, while others enable collaborative analysis on privately-held datasets, allowing data to be used without disclosing copies of data. PETs are multi-purpose: they can reinforce data governance choices, serve as tools for data collaboration or enable greater accountability through audit. For these reasons, PETs have also been described as “Partnership Enhancing Technologies” or “Trust Technologies”.

    What is data privacy, and why is it important?

    The data we generate every day holds a lot of value and potentially also contains sensitive information that individuals or organisations might not wish to share with everyone. The protection of personal or sensitive data featured prominently in the social and ethical tensions identified in our 2017 British Academy and Royal Society report Data management and use: Governance in the 21st century.

    How can technology support data governance and enable new, innovative uses of data for public benefit?

    The Royal Society’s Privacy Enhancing Technologies programme investigates the potential for tools and approaches collectively known as Privacy Enhancing Technologies, or PETs, in maximising the benefit and reducing the harms associated with data use.

    Our 2023 report, From privacy to partnership: the role of Privacy Enhancing Technologies in data governance and collaborative analysis (PDF), was undertaken in close collaboration with the Alan Turing Institute, and considers the potential for PETs to revolutionise the safe and rapid use of sensitive data for wider public benefit. It considers the role of these technologies in addressing data governance issues beyond privacy, addressing the following questions:

    • How can PETs support data governance and enable new, innovative uses of data for public benefit? 
    • What are the primary barriers and enabling factors around the adoption of PETs in data governance, and how might these be addressed or amplified? 
    • How might PETs be factored into frameworks for assessing and balancing risks, harms and benefits when working with personal data? 

    In answering these questions, our report integrates evidence from a range of sources, including the advisement of an expert Working Group, consultation with a range of stakeholders across sectors, as well as a synthetic data explainer and commissioned reviews on UK public sector PETs adoption (PDF) and PETs standards and assurances (PDF), which are available for download.

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