Accelerating the commercialisation of cyber innovations: CyberASAP's latest cohort

Posted on: 16/05/2023

This week, CyberASAP has launched its latest cohort consisting of 27 academic projects. The programme is set to run from May 2023 to March 2024 and is divided into two phases.

Phase 1, referred to as the Value Proposition, requires the teams to create a value proposition and validate it in the market. This is followed by the Market Validation phase. Phase 2 provides funding for the development of a Proof of Concept, which is critical for the projects’ commercialisation success.

The Department for Science, Innovation and Technology (DSIT) and UK Research and Innovation (UKRI) plan to invest over £1m in the most promising commercial opportunities, with the goal of accelerating the commercialisation of cyber innovations from UK academic Knowledge Bases into the wider market. This investment will support CyberASAP in achieving its mission of facilitating the development of academic projects into commercial opportunities, including licence opportunities and successful spin-outs.

This year, CyberASAP has continued its commitment to include projects from the Security of Digital Technology at the Periphery (SDTaP) initiative, which includes the PETRAS IoT Research Hub. The SDTaP competition, which is funded by UKRI, provides funding to business-led demonstrators that address cyber security challenges on the Internet of Things. This inclusion further enhances the opportunities for academic projects to successfully commercialise their research through the CyberASAP programme.

We’re thrilled to be launching our latest cohort and continuing CyberASAP’s mission to support academic projects in commercialisation of their research and helping them work towards becoming With the support of DSIT and UKRI, we are excited to see the impact our programme will have on accelerating the commercialisation of cyber innovations from UK academic Knowledge Bases into the wider market.

– Emma Fadlon, Co-Director, CyberASAP

The teams and projects for CyberASAP 2023/24 are:

  • Anglia Ruskin University – p-CTI: Privacy–Aware Cyber Threat Intelligence Information-Sharing Platform
  • Anglia Ruskin University – QuantoSniff: A Next Generation Cyber Defence using Quantum-Safe Cryptography
  • Aston University – Intelligence Informed Scenario-Based Pentesting Tool
  • Cardiff University – HXAI-VDI: Human-cntric XAI enabled Vulnerability Detection and Identification in the Internet of Things (IoT)
  • De Montfort University – DaSIPreS: Data Driven Cyber Security Incident Prediction for IT SMEs
  • De Montfort University – Speak-to-Secure (S2S): A Natural Language Human-Computer Interaction To Secure Cyber Physical Systems
  • Edinburgh Napier University – TrueDeploy
  • Edinburgh Napier University – TrustShare: Privacy-preserving and Trusted Threat Intelligence Sharing using Distributed Ledgers
  • Kingston University – Ontology-based SirenPod – AI-powered Honeypot for Medical Devices
  • Middlesex University – Capable
  • Middlesex University – AI-bility 4D
  • Newcastle University – PReSense: Privacy-Preserving and Regulation-Aware indoor monitoring sensors
  • Nottingham Trent University – Drive with Confidence: A Safe and Secure Driving System to Mitigate Remote Vehicle Hijacking Risks
  • Queen Mary University of London – Blockchain-based trusted platform for servers and devices security
  • The University of West London – IoT Armor: An IoT Secure-by-Default Educational Toolkit
  • University of Central Lancashire – BlockFortify: Building Digital Fortresses for Phishing with Blockchain
  • University of Essex – Data/AI Secure-by-Design Orchestration Platform (DAISOR)
  • University of Essex – Cyber hygiene self-assessment maturity tool
  • University of Essex – FORENSIC: Fast and Autonomous Platform Anomalies detections in Cyber Physical Systems
  • University of Hertfordshire – Cyber Essentials Intelligent Self-Assessment Assistant (CEISAA)
  • University of Oxford – DLT Cybersecurity Monitoring
  • University of Oxford – Vouchsec – Conversational Network Detection & Response against AI-powered Threats
  • University of Oxford – CyberHeels
  • University of Sheffield – ATM: Automated Threat Modelling for Enterprise AI-enabled Assets
  • University of Strathclyde – Using synthetic data and unsupervised learning methods for malware detection
  • University of The West Of Scotland – QuantumBlockVault: Post-Quantum Resistant Blockchain for Securing Business-critical Data
  • University of Wolverhampton – VPTaaS: Cyber Penetration Test as a Service for Future Vehicles

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