Objective
ThreatMark vision is to secure the assets of people/companies by better protection of digital transaction systems against cyber-attacks. It dramatically improves the detection & protection capabilities of cyber-operators against threats, fraud & incidents. It allows them to increase their security by complex preparedness, rapid detection and faster response.
Advanced machine learning and unique algorithms of ThreatMark make the detection of advanced threats and behavioral anomalies more sensitive and reliable while lowering the cost of operation. We challenge the conventional methods of transaction protection by bringing usually fragmented features under one roof: (online) fraud detection systems, web fraud detection, web application firewall, malware detection, criminal and account takeover detection.
This is unique and appreciated by users, as proven by recent competitor analysis. The solution has been designed to answer the business opportunity that lays in plausible cyber-security market trends:
(1) Steady growth of online transactions & cyber attacks/ online fraud at the same time;
(2) Rise of as-a-service model providers & market (9.8%/ p.a.);
(3) Pressure to decrease high expenses for complex security.
The ultimate goal of this project is to bring to market system ThreatMark capable of improving the security of transactions and decreasing the resources needed. Four target groups were identified: on-line banks, high value transactions providers, secure apps, emerging digital services. Some strategic alliances with business partners exist.
The sub-objectives of FS include requirements analysis, detailed business plan, technology roadmap update and company development strategy based on innovation management training.
The company has already invested into its technology more than 200 000 EUR (equipment, travel, 1 500 own man-days, 2 000 man-days of academic partners from 2013). To fully enter the market in 2017 a strategic investment or funding is requested.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencescomputer and information sciencescomputer securitymalicious software
- social scienceseconomics and businessbusiness and managementinnovation management
- natural sciencescomputer and information sciencescomputer securitynetwork security
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
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Programme(s)
Funding Scheme
SME-1 - SME instrument phase 1Coordinator
619 00 BRNO
Czechia
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.