SECUREWORLD

consortium of technology companies committed to information security

The project focuses on industrial research in cybersecurity, data privacy and governance technologies, as well as user training. Its goal is to address the challenges faced by Spanish companies in digital interactions within a hyperconnected world and a data-driven economy.

Challenges

Ensuring the origin and handling of data by clearly identifying the agents or entities involved in its collection, storage and communication, so that none of these actions can later be repudiated.

Providing mechanisms to guarantee the level of privacy required according to the nature, ownership and intended use of the data, while always complying with applicable regulations and contractual confidentiality requirements.

Enabling mechanisms to store and transmit data securely, and above all, to make it available to potential users in the required form for its possible exploitation.

Raising awareness among all those involved in data processing that data is an asset to be managed with the utmost care and respect, always ensuring its security.

Solution

Development of technology to generate solutions that allow both qualified and non-qualified staff to be trained in attack and defence techniques, as well as to improve systems themselves in order to facilitate interpretation and interaction during attack and prevention scenarios:

Blockchain technology is applied to improve data sovereignty management, addressing the problem of data custody and management effectively, and overcoming the traditional approach focused solely on functional aspects of data exploitation.
Research and use of non-conventional data encryption algorithms and techniques, such as elliptic curve cryptography and the concept of contextual challenges, in order to develop or strengthen the security of protocols and file systems.
Application of AI techniques as a mechanism to complement continuous multi-factor authentication systems, detect anomalies, attack patterns and recurring concept drifts that can reliably be identified as threats, so that data operations (algorithms) remain protected.