Good AI and Cybersecurity Relies On Resilient Data
General awareness of the technology landscape is currently driven by ongoing coverage on two sectors: AI and cybersecurity. AI has captured the attention of industry leaders and media alike resulting in comprehensive research initiatives such as those of the Australian National University, and national security efforts from the Australian Cyber Security Centre continue to improve and evolve.
While AI and cybersecurity continue to dominate news headlines, one critical aspect of digital infrastructure is often overlooked: data resilience. Data resilience ensures the efficacy of these two technologies. By providing continuous availability and integrity of data, data resilience mitigates the risks of data loss and downtime, underpinning the reliability of these advanced systems. Understanding and emphasising the role of data resilience is essential for a holistic and sustainable digital strategy.
Enhancing AI and Cybersecurity Through Data Resilience
Data resilience refers to the ability of an organisation to protect, access, and recover its data during and after disruptions and is indispensable for both AI and cybersecurity. AI systems thrive on vast amounts of data, requiring continuous availability and integrity to function effectively. Any interruption in data flow can lead to significant setbacks, reducing the accuracy and reliability of AI predictions and decisions. Similarly, for cybersecurity, data resilience is critical. Effective cybersecurity measures depend on the availability of accurate and up-to-date data to identify threats, analyse vulnerabilities, and respond to incidents.
A resilient data infrastructure ensures that data is always available when needed, protected from loss or corruption, and quickly recoverable in the event of a disruption. This robustness enhances the performance of AI algorithms by providing uninterrupted access to high-quality data and strengthens cybersecurity defences by ensuring that critical data is safeguarded and recoverable.
With the recent acquisition of Coveware, Veeam has significantly bolstered its data resilience capabilities, particularly in the realm of ransomware recovery and incident response. Covewareโs expertise in cyber-extortion response, forensic analysis, and remediation will be integrated into Veeam’s offerings, providing customers with the industryโs first true end-to-end ransomware protection and recovery. In addition to best-in-class Incident Response, Coveware has the largest and constantly evolving commercial database of ransomware threat signatures, and further strengthens Veeam Data Platformโs AI-driven threat detection engine, ย ensuring that businesses can maintain robust AI operations and strong cybersecurity postures even in the face of sophisticated attacks.
Common Misconceptions About Data Resilience
The more valuable your backup is, the more likely it is a target. The Veeam 2024 Ransomware Report revealed backup repositories are targeted in 96% of attacks, with bad actors successfully affecting the backup repositories in 76% of cases. This is why data resilience is crucial.
Despite its importance, data resilience is often misunderstood. It’s more than simple data backup; it also includes data recovery, freedom, security and intelligence
Data resilience is often overlooked because itโs seen as a back-end concern and lacks the visibility of AI and cybersecurity innovations. This gap in understanding can lead to insufficient investment and prioritisation within organisations.
Investment Prioritisation Strategies
Organisations need to adopt a more integrated approach to digital strategy where they recognise the interdependence of AI, cybersecurity, and data resilience. Prioritising investment in data resilience involves several key strategies:
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Assessment and Planning: Conduct thorough assessments to identify potential risks and vulnerabilities in data management and develop comprehensive data resilience plans.
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Proactive Measures: Implement proactive measures such as regular data backups, disaster recovery drills, and continuous monitoring to prevent data loss and ensure quick recovery.
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Technology Integration: Leverage advanced technologies and tools that integrate data resilience with AI and cybersecurity, creating a cohesive and robust digital infrastructure.
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Training and Education: Educate teams and stakeholders about the importance of data resilience, providing training on best practices and the latest tools and techniques.
Educating Teams and Stakeholders
Education is crucial in shifting the perception and understanding of data resilience within an organisation. This involves not only training IT and cybersecurity teams but also engaging executives and decision-makers in conversations about the strategic importance of data resilience. Highlighting real-world examples of data resilience in action, and its impact on AI and cybersecurity, can drive home the message and encourage broader support and investment.
As the digital landscape continues to evolve, the interdependence of AI, cybersecurity, and data resilience becomes increasingly evident. By broadening the conversation to include data resilience and prioritising its implementation, organisations can build a more robust, secure, and effective digital infrastructure. Data resilience is not just a supporting player; it is the foundation that enables AI and cybersecurity to reach their full potential, ensuring continuous innovation and protection in an ever-changing technological world.
