Detect anomalies, stop attacks, and protect critical banking systems with AI-driven monitoring for devices, networks and digital twins.
A security layer designed for IoT devices, banking infrastructure and their digital twins.
Monitor ATMs, POS terminals and sensors for abnormal behaviour in real time.
Detect fake or poisoned data before it reaches your simulations and risk models.
Use ML models to flag unusual activity across logs, metrics and network traffic.
Give engineers and auditors clear reasons why behaviour is flagged as risky.
Built for organisations that need visibility and trust across complex, connected systems.
Built from active research in IoT, digital twins and AI security in the banking sector.
Clear, human-readable explanations suitable for risk, compliance and regulators.
Designed to plug into your existing infrastructure and grow with your digital strategy.
Short explainers, research highlights and practical guidance on securing IoT and digital twins in banking.
A high-level post explaining why ATMs, POS terminals and sensors are attractive targets for attackers.
What can go wrong when attackers poison data feeding your digital twins and risk models.
Why explanations matter for auditors, regulators and incident response – and how JNTH approaches it.
Interested in pilots, collaboration or research partnerships? Let’s talk.
Email: security@jnthsecurity.com
Phone: +44 0000 000000
Location: London, United Kingdom
Here we will later add a contact form powered by the JNTH Security backend.