In an era where security and data protection are converging, the traditional approaches are no longer sufficient.
By Kate Mollett, senior director at Commvault Africa
The escalating vulnerability of data necessitates a proactive and integrated defence strategy. As the threat landscape evolves, it’s no longer a question of if an attack will occur, but when.
To identify, stop, and respond to cyberthreats, businesses must implement cutting-edge technology and frameworks. This includes using technology such as machine learning (ML) and artificial intelligence (AI) algorithms to analyse enormous volumes of data and find odd patterns suggestive of possible attacks.
Furthermore, businesses ought to use threat intelligence solutions that offer real-time insights, enable proactive threat hunting, and enable quick reactions to new threats.
AI’s empowerment of hackers
In today’s digital landscape, it’s crucial to acknowledge that AI and ML, like any other software, are not immune to hacking.
The rise of AI has inadvertently empowered hackers with unprecedented capabilities to penetrate secure environments. Malicious actors can now carry out assaults with greater sophistication and efficiency by utilising AI. Automating hostile behaviour, broadening the scope of vulnerable exploits, and getting beyond traditional security controls are all examples of this.
As a result, this worrying trend not only makes cyberthreats more frequent and severe, but it also creates brand-new attack routes that were previously unimaginable.
Furthermore, AI itself poses a risk to data integrity. As AI algorithms process and generate vast amounts of data, there is an inherent challenge in ensuring the accuracy, privacy, and security of this data.
Traditional security measures may be overwhelmed by the speed with which AI systems generate data, making it more difficult to identify and stop unauthorised access, data breaches, or manipulations. Early anomaly detection is emerging as a crucial capacity to recognise dangers, act quickly, and reduce data loss.
Businesses may actively monitor and analyse enormous amounts of data in real-time by utilising AI and ML algorithms, enabling the prompt detection of suspicious behaviours or aberrant trends. This proactive approach enables swift mitigation measures to be implemented, significantly reducing the potential impact of cyberattacks and safeguarding sensitive data from unauthorised access or manipulation.
Data breach risks and the urgency of proactive protection
With limited resources and threats emerging from various fronts, the pursuit of data has become the prime motive for cyber threats. Ranging from zero-day vulnerabilities to easily accessible ransomware-as-a-service kits available at unbelievably low costs, businesses are confronted with multifaceted risks.
The repercussions of data breaches, such as offline backups being compromised or sensitive information being leaked on the dark web, pose significant threats to the reputation and operations of businesses.
Empowering security teams to unveil previously concealed threats and granting IT teams the capability to respond swiftly are key components of this proactive approach. In this context, closer collaboration between IT and security becomes essential. Particularly in an era marked by downsizing, reduced team sizes, and limited expertise, integrating the functions of security and IT becomes paramount.
Therefore, recognising the ongoing breaches by malicious actors and the limitations of security tools, the focus on proactive data protection and recovery gains significance. This approach aims to mitigate the fallout from potential breaches and foster a stronger partnership between IT and security teams to effectively address the challenges posed by an evolving threat landscape.
Building resilience
Rather than waiting for an attack to be detected, Commvault’s ThreatWise provides alerts as bad actors navigate within your network, identifying suspicious activities before substantial damage occurs.