Project description
Data protection on track
The more digital technology advances, the larger the volume of sensitive information businesses aggregate and analyse, and the tougher it is to protect this data. Failure to protect sensitive data may give rise to hefty fines and lasting damage to a company’s reputation and brand. The EU-funded project Data TrackerTM is developing technology to help companies identify sensitive data. Their MinerEye Data Tracker™ is based on interpretive AI technology. It uses computer vision and machine learning to crawl, identify, and classify all company data. Going down to the pixel level, it generates “fingerprints” of the data, creating a learning process for content optimisation.
Objective
The basis for properly protecting data relies on being able to dynamically identify it and understanding the way it behaves,
however companies fail in achieving this today. Current solutions and technology constraints compel chief data officers
(CDO) and chief information security officers (CISO) to spend massive amount of money and resources to define and
identify sensitive data.
MinerEye has developed a proprietary technology to match data to a reference set using advanced technics applied
originally in computer vision applications and machine learning solutions, to automatically categorize, classify and track
unstructured data. This set of algorithms read the bytes of a given file and represent its content by creating a single
mathematical vector on the fly, that is constant in size and very small (few k’s) per each file.
From this point on, the system (DataTracker™) uses this vector called “signal”, that is extracted from every file it scans, for
its unsupervised clustering and further analysis tasks. This capability allows the system to process unprecedented amount of
data in a very short period (~1TB/3hrs.). The system does not dispose files from their original storage / location, opens or
changes the file but rather reads their byte stream, creates the signal on the fly and sends it out to the server. This saves
enormous network load when learning the sensitive data patterns and attributes and strengthens the non-intrusive nature of
the system. The signal can be refreshed on any scheduled basis since the data does not change in such a pace that would
affect its accuracy in the clustering process. Additionally, the scheduled scan is incremental. Powered by Interpretive AI™
Technology, MinerEye sees beyond form and file, tracking sensitive data by its essence. MinerEye does not just see
numbers, names, and file types. It sees contracts, customers’ personal data, chemical patents, most sensitive designs and
sketches, and more.
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. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences artificial intelligence computer vision
- natural sciences computer and information sciences artificial intelligence machine learning
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.2.3. - INDUSTRIAL LEADERSHIP - Innovation In SMEs
MAIN PROGRAMME
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H2020-EU.3. - PRIORITY 'Societal challenges
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H2020-EU.2.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
SME-2 - SME instrument phase 2
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-EIC-SMEInst-2018-2020
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
459005 HOD HASHARON
Israel
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.