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Stopping ransomware in its tracks: New enterprise app integrates AI & University research

April 19, 2024
in Technology and Engineering
Reading Time: 5 mins read
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Is it malware or not? Is it safe to run?
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17 April 2024, Luxembourg and Potomac Falls, USA – CYSANA (CYberSecurity ANAlytics) is a new AI-based enterprise solution to protect against malware and ransomware announced today by the cybersecurity company Conatix, in collaboration with the University of Luxembourg’s Interdisciplinary Centre for Security, Reliability and Trust (SnT).

Is it malware or not? Is it safe to run?

Credit: CYSANA © Conatix

17 April 2024, Luxembourg and Potomac Falls, USA – CYSANA (CYberSecurity ANAlytics) is a new AI-based enterprise solution to protect against malware and ransomware announced today by the cybersecurity company Conatix, in collaboration with the University of Luxembourg’s Interdisciplinary Centre for Security, Reliability and Trust (SnT).

CYSANA stops malware and ransomware before they have an impact on business. It does this by integrating the most recent developments in deep learning neural network-based image classification and anti-encryption research.

The core of CYSANA lies in its AI module, which uniquely visualizes software applications as images to detect malware embedded in executable files at the point of download, before these files open, install or engage in any activity on a computer. The CYSANA anti-encryption module further strengthens this defense by preventing malware from using a computer’s own encryption keys to encrypt user data and hold it for ransom, effectively blocking malware from any source from becoming ransomware.

 Is it malware or not? Is it safe to run?

Malware and ransomware pose two of the greatest, and fastest-growing, cyber threats in the world today. Malware can be hidden in executable software files and remain undetected for long periods while monitoring user activity and corporate operating procedures or stealing or deleting data. In its most antagonistic form, malware transforms into ransomware, encrypting valuable data on computers, often demanding a ransom to reverse the damage.  In July 2023, Reuters reported close to $450 million  had been paid to ransomware attackers in the first half of that year, an increase of $175 million over the same period in 2022.  The impacts of both malware and ransomware can be devastating to companies and government agencies, with attacks becoming more frequent, sophisticated and costly. 

 

CYSANA Empowers Cybersecurity Excellence with an Innovative Approach to Advancing Expertise

“Our innovative CYSANA software merges deep learning and anti-encryption technologies to offer a new level of robust cyber protection,” said David Lehrer, CEO of Conatix. “Developing this solution has been a true collaboration resulting in more robust and encompassing cyber protection than a single company could develop on its own.”

“SnT strives to conduct research with an impact, and this product launch is a significant success story for that mission,” said Dr. Carlo Duprel, head of the SnT’s Technology Transfer Office of the University of Luxembourg. “The collaboration with Conatix to launch CYSANA to a worldwide market underlines our depth of expertise in the field of cybersecurity, and commitment to combatting cybercrime.”

In the development process CYSANA’s neural network models were trained and tested on the Luxembourg-based MeluXina supercomputer operated by LuxProvide. This high-performance computer testing ground, one of the most powerful in Europe, helped make the product effective at detecting novel and zero-day malicious files. 

“LuxProvide is passionate about driving innovation and research, as demonstrated by our significant support for the CYSANA project, along with our commitment to offering a leading platform for digital and other research initiatives.” stated Arnaud Lambert, CEO of LuxProvide.

With the launch of CYSANA, Conatix is offering a deep learning AI-based solution against some of the hardest-to-find malware, a solution that is faster and more effective than existing anti-malware systems. CYSANA is a barrier for those malware that could become ransomware and start encrypting valuable company data. The anti-ransomware solution within the Cysana product is patented by the University of Luxembourg in 15 countries. Cysana’s exclusive license with the University of Luxembourg’s SnT is another step from the Centre to strengthen the impact of its research at a global scale.

As cyber threats like malware and ransomware escalate, the Conatix CYSANA software offers a vital solution to protect businesses and government agencies. It recently won the AI & Data category of the 2024 Product Awards, delivered by Products That Count. The initial release of Cysana is directed at selected cybersecurity service providers (MSPs) and CISO teams in North America and Europe by invitation only.

 


 

Conatix has won numerous international innovation awards, including being named one of the most innovative cybersecurity startups in the UK by the UK government cybersecurity directorate two years in a row and being listed in the global CyberTech 100 list of the most innovative cybersecurity startups in the world for banking.  Conatix is an early-stage AI for cybersecurity startup based near Washington DC, and in New York, Montreal, London and Berlin.  Collaboration by Conatix with the University of Luxembourg on this software product R&D was supported by the EIT Digital Innovation Factory innovation grant program part-funded by the European Union.  www.cysana.co and www.conatixcyber.com 

LuxProvide is at the forefront of digital intelligence, combining data science expertise with supercomputing capabilities. Centered around MeluXina, Luxembourg’s advanced supercomputer, LuxProvide focuses on accuracy, security, and sustainability in the digital realm. The company transcends traditional technological boundaries, fostering innovative solutions that elevate the human experience and drive positive change. LuxProvide is dedicated to pioneering a future where technology not only evolves but enhances every aspect of life. Learn more:

The Interdisciplinary Centre for Security, Reliability and trust (SnT) of the University of Luxembourg, founded in 2009, promotes and conducts research in socio-technical security and cybersecurity in collaboration with other disciplines.  The Sociotechnical Cybersecurity (IRiSC) research group within SnT conducts forward-looking theoretical and experimental research on cybersecurity and online privacy based on the interdisciplinary expertise of its members.  IRiSC integrates methods from social sciences and legal analysis into computer science to address the complexity of reliable, secure and trustworthy systems and the multiple factors leading to misuses and cyberattacks.

The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character. The University was founded in 2003 and counts close to 7,000 students and more than 2,400 employees from around the world. The University has three missions: research, higher education, and contribution to the social, cultural and economic development of the country. The University’s strategic development areas are digital transformation, medicine and health, and sustainable and societal development. The University has three faculties (Science, Technology and Medicine; Law, Economy and Finance; Humanities, Education and Social Sciences) and four interdisciplinary research centres (Interdisciplinary Centre for Security, Reliability and Trust – SnT; Luxembourg Centre for Systems Biomedicine – LCSB; Luxembourg Centre for Contemporary and Digital History – C²DH; Luxembourg Centre for European Law – LCEL). The University offers 18 Bachelor and 46 Master study programmes, and has four doctoral schools. Times Higher Education ranks the University of Luxembourg #4 worldwide for its “international outlook,” #25 in the Young University Ranking 2023 and among the top 250 universities worldwide.

 

 



Method of Research

Imaging analysis

Subject of Research

Not applicable

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