Overcoming data sharing & transfer risks with Multi Party Computing
Wouter Seinen from Pinsent Masons Netherlands and Ian Wachters from Roseman Labs discuss the MPC human trafficking use case in this interesting article on how this privacy enhancing technology enables parties owning different sets of sensitive data to collaborate and generate insights without actually sharing their data with each other.
Read the Article from Data Cybersecurity & Privacy magazine.
KC Mission 2020 Data and Intelligence Grant Awarded
AI4Intelligence: From Multimodal Data to Trustworthy Evidence in Court
Sustainable Rescue Foundation is honoured to be part of the consortium for the grant awarded to the University of Amsterdam. We look forward to participating in this innovative use of AI to raise convictions.
The sheer mass and variety of data from multiple sources has created a key challenge to police and prosecution to gain criminal convictions. Investigative teams face a labor-intensive manual task to sift through millions of data points to obtain effective court evidence. AI4Intelligence addresses the conversion of gathered multimodal data into trustworthy evidence ready for court. An innovative AI-driven toolset with advanced visualizations transforms massive amounts of data into an asset that supports intelligence professionals in their quest for relevant evidence in an efficient, fair, accountable, and transparent manner. For effectiveness, AI4Intelligence will explore compliance issues for digital evidence and merge technical aspects with legal procedural requirements. Deliverables will consist of AI and visualization software, guidelines for intelligence professionals, a legal framework including its representation in the CASE standard for digital evidence (caseontology.org), and a unified technical infrastructure. Development of tools and their evaluation will be carried out through collaboration with police investigators and court officials using two exemplary use cases namely online child abuse and criminal infrastructures such as underground digital marketplaces and messaging services used by criminals. The project is conducted in a highly interdisciplinary, balanced and dedicated consortium with 4 general/technical and 2 applied universities, 4 SMEs, 1 large company, 3 law enforcement agencies and TNO. The technical impact of AI4Intelligence will build a scalable foundation of effective machine-to-human interplay in fighting crime. The social impact is faster time to court with effective use of data to convict criminals and to reduce child abuse.
Financial Crime Week 2022
Whether it’s about drug crime, human trafficking, fraud, money laundering or cybercrime, everyone agrees on one theme: the financial benefits are enormous. Experiences in recent years also provide another worrying conclusion: the degree of interconnection is increasing at an alarming rate on many fronts. A few examples: increasing criminal investments in amateur sports clubs, illegal earnings from labor exploitation flowing into real estate and drug criminals committing mortgage fraud. If you could track an illegally earned euro, this would result in a complex and difficult to trace route. The boundaries between legal and illegal, upper and underworld, online and offline, national and international are blurring. In short, the intertwining is complete. How do we combat these complex forms of financial crime? What do we actually know about them? Are there best practices? During Financial Crime Week 2022, experts will come together to shed light on these questions.
Paul Fockens will present the Multiparty Computation use case during a breakout session.
Using MPC technology to enhance privacy in data sharing
The April 2022 Privacy Laws & Business International Report features how Sustainable Rescue Foundation, Roseman Labs, the Data Sharing Coalition and Pinsent Masons showed how the encryption-based Multi-Party Computation (MPC) technology enables data collaboration without the parties actually sharing the personal data.
Read the article by Linda Linkomies MPC Tech (PL&B)