CRITIS 2026: diva.exchange and HSLU Redefine Network Resilience Through Uncertainty

The diva.exchange project continues its academic collaboration and open-source research in the field of distributed network security. In 2026, researchers from the Lucerne University of Applied Sciences and Arts (HSLU) and diva.exchange will present key findings at the prestigious European conference CRITIS 2026 (Critical Information Infrastructure Security), dedicated to the security of critical infrastructures.

The presentation is based on our peer-reviewed research: “Extending Resilience through Uncertainty in Fully Distributed Systems” by Patrick Grossenbacher, Konrad Bächler, and Dieter Arnold.

What is the presentation about?

Fully distributed peer-to-peer (P2P) networks, such as the Invisible Internet Protocol (I2P), eliminate single points of failure to protect critical communication infrastructure. However, distribution alone does not guarantee survival if communication topologies are exposed to targeted disruptions.

The paper extends the definition of functional resilience: in distributed systems, anonymity, expressed as adversarial uncertainty, is a strict prerequisite for keeping services operational. If an adversary can map logical routing paths, low-cost targeted attacks become viable.

Innovative Approach & Key Findings:

  • Quantifying Anonymity Resilience: We introduce an information-theoretic framework based on conditional entropy to measure how much uncertainty a passive adversary retains about hidden communication tunnels.
  • Two-Stage Machine Learning Framework: Using metadata and timing side-channels (without payload decryption), we evaluate an inference pipeline combining an optimized Gradient Boosting packet detector with a consensus-based path reconstructor.
  • The Role of Consensus: While a single passive observation leaves high uncertainty, path recurrence over time enables an adversary to build consensus; drastically reducing uncertainty even under partial network observability.

Why does this matter for the community?

To build truly resilient, privacy-preserving distributed protocols, such as the infrastructure empowering diva.exchange, we must understand how probabilistic traffic analysis degrades network unobservability. Quantifying anonymity resilience allows developers to design proactive countermeasures against modern passive surveillance.

The complete dataset, measurement framework, and evaluation code are available as open source.

Join the diva.exchange session at CRITIS 2026 to explore cutting-edge research at the intersection of network security, resilience engineering, and decentralized systems.

Official Conference Program: https://critis2026.com/program

THIS IS DIVA.EXCHANGE

The non-profit association diva.exchange, Switzerland, uses a barrier-free and collaborative approach to create free banking technology for everyone. Open-source technology ensures the privacy of all participants in the financial system of the future. The blockchain-based system is fully distributed. Everyone can participate in diva.exchange.

Diva.exchange is committed to the belief that only commercially free technology can reliably protect user privacy.

Collaboration with the scientific community plays an important role in the development of diva.exchange. The results of diva.exchange research are constantly being validated by academic institutions and publicly presented at specialized conferences.

LEARN MORE ABOUT OUR WORK

All technical information is available at: https://github.com/diva-exchange/

I2P beginner’s guide and installation guide:https://www.diva.exchange/en/privacy/introduction-to-i2p-your-own-internet-secure-private-and-free/

All videos are here: https://odysee.com/@diva.exchange:d/

Introduction to I2P: https://en.wikipedia.org/wiki/I2P

Testnet of diva.exchange: https://testnet.diva.exchange

CONTACT US

Twitter: https://twitter.com/@DigitalValueX

Mastodon: https://social.diva.exchange/@social

If you still have questions you can always find us on Telegram: https://t.me/diva_exchange_chat_de (in English, German, or Russian)