Data sharing in trusted networks

One of the most impactful developments in security we have seen over the past few decades is the emergence of trusted networks for information sharing and collaboration. Two of the most important ones are Information Sharing and Analysis Centers (ISACs) and peer networks. As the National Council of ISACs explains, “Information Sharing and Analysis Centers help critical infrastructure owners and operators protect their facilities, personnel, and customers from cyber and physical security threats and other hazards. ISACs collect, analyze, and disseminate actionable threat information to their members and provide members with tools to mitigate risks and enhance resiliency. ISACs reach deep into their sectors, communicating critical information far and wide and maintaining sector-wide situational awareness”. ISACs solve the problem of trust when it comes to threat intelligence sharing and collaboration. Historically, security leaders sworn to secrecy and bound by non-disclosure obligations had no incentives to share their most sensitive findings. There was always a danger that their attempt to be helpful would backfire and expose them to personal and professional liability. Since ISACs are supported by the government, they make it possible for CISOs to open up with their trusted peers in ways they are not able to do anywhere else. The Financial Services Information Sharing and Analysis Center (FS-ISAC), founded in 1999, has long been an example of what success can look like, and there are now tens of ISACs active in other segments. Many other forms of collaboration take part in peer networks for CISOs and security practitioners. Usually, these are invite-only communities that congregate in Slack, WhatsApp, Discord, or on proprietary platforms and encourage professional collaboration. While these communities are invisible and inaccessible to outsiders, they play an important role in the dissemination of best practices, peer support, aggregation of feedback about vendors, professional development, and more.

Safeguarding information while enabling collaboration requires methods that respect privacy, ensure accuracy, and sustain trust. Privacy-Enhancing Technologies create conditions where data becomes useful without being exposed, aligning innovation with responsibility. When companies exchange sensitive information, the tension between insight and confidentiality becomes evident. Cryptographic PETs apply advanced encryption that allows data to be analyzed securely, while distributed approaches such as federated learning ensure that knowledge can be shared without revealing raw information. The practical benefits are visible in sectors such as banking, healthcare, supply chains, and retail, where secure sharing strengthens operational efficiency and trust. At the same time, adoption requires balancing privacy, accuracy, performance, and costs, which makes strategic choices essential. A thoughtful approach begins with mapping sensitive data, selecting the appropriate PETs, and aligning them with governance and compliance frameworks. This is where technological innovation meets organizational responsibility, creating the foundation for trusted collaboration. #PrivacyEnhancingTechnologies #DataSharing #DigitalTrust #Cybersecurity

Finally. It’s happening. Live data-sharing to fight fraud – at scale. 🚨 This week, major UK banks and tech giants like Amazon, Google, Meta, and Match Group committed to real-time sharing of fraud indicators – suspicious URLs, abnormal transaction patterns, scam signals. All automated. All cross-sector. All in real-time. This is a massive leap forward. But it also raises one important question: What took us so long? Back in 2020, we were already talking about how painfully slow and fragmented AML intelligence sharing was. In some cases, the time lag made it nearly impossible to recover stolen funds or stop fraud rings mid-operation. Here’s what’s different now: Automated systems now push tens of thousands of fraud indicators per day – compared to almost nothing in the initial pilot. It's cross-sector: banks + tech + telecoms. It’s real-time – not days or weeks after the scam. 🔗 Full FT story: https://lnkd.in/eVKKaWuH But let’s not stop at headlines. Because real impact happens when fraud teams can: ✅ Freeze money before the victim even reports the scam ✅ Investigate collaboratively across borders and silos ✅ Stop the same mule network from cashing out at multiple institutions This is exactly what we built Salv Bridge for. Our clients are already seeing up to 80% fund recovery rates, compared to the industry average of 5%. It’s not magic – it’s structured collaboration, fast action, and trust across institutions. The UK's new pledge is a milestone. But it must be more than a press release. Without pressure from regulators and continued cross-industry commitment, we risk another pilot that fizzles out. 💬 What will it take to make real-time, cross-industry intelligence sharing business as usual in fraud prevention? 👇 Would love to hear from banks, fintechs, and policymakers here. #AML #fraudprevention #fintech #regtech #intelligencesharing #SalvBridge #FinancialCrime #UKfraud #APPfraud

Secure access to unusable data is still unusable data. If we're serious about accelerating innovation in diagnostics, we need to build Trusted Research Environments (TREs)—secure, privacy-compliant, and governed systems where data can be shared and analyzed without being moved or duplicated. These environments aren’t just about infrastructure; they’re about trust. They ensure that: Patient data is protected by design Researchers and AI teams get secure access to high-quality, real-time data Compliance, governance, and auditability are built in from the ground up But more importantly, TREs don’t solve the problem alone. They only work if the data within them is trustworthy, complete, and ready for analysis. #biomedicalresearch #diagnostics #clinicalresearch #healthcare #datainnovation #AI #ML #Models #DataAnalysis #TREs #Research #Medicine

How Responsible Data Sharing Works 🔐 Responsible data sharing starts with privacy At NatWest Group responsible data sharing is built on privacy first. Through our partnership with Smart Data Foundry, we’ve created a model for sharing financial data in a way that drives positive societal impact without compromising trust. • Data is anonymised/deidentified and aggregated – No personal information is ever shared. Instead, we provide trends and patterns that help researchers and analysts understand the consumer financial landscape across the UK. • Strict governance – This data is accessed through secure, trusted research environments, ensuring it’s only used for approved research projects. • Clear purpose and impact – Every data project has a societal goal, from understanding areas of financial vulnerability to supporting targeted interventions and more. We’re committed to proving that data can be a force for good without compromising trust or privacy. #ResponsibleDataSharing #DataPrivacy #PrivacyByDesign #DataForGood