Today, it can be said that data is now what makes our world go round. Each individual continues to create more data with each passing day, and organisations have more access to such data than ever before. Given how data is now worth its weight in gold, it is everyone’s responsibility to become data literate, particularly in understanding how the data economy works and how their own data and information play a role in it.
Neglecting this responsibility will eventually lead to catastrophic consequences that can derail one’s life or business, be it due to data breaches, identity theft, and so on. This is where data protection comes in to safeguard data from loss, damage, threats, or compromise. In other words, it is the shield that ensures data remains private and handled properly.
Data protection is interdependent with data privacy, which is concerned with outlining the ‘what’ and ‘why’ of data handling. In contrast, data protection provides the ‘how’ or the practical measures that enforce privacy policies, as the latter alone cannot inherently guarantee data security. With this distinction out of the way, let us now explore some of the current trends that may well become the best practices for data protection in 2024.
1. Consolidate security platforms
The seamless user experiences that customers demand come at the cost of increased complexity – the archenemy of security. As cloud-native digital environments advance but also invite more risk, security teams (who are more often than not stretched to their limits) will struggle with an abundance of controls.
This will eventually renew the push for simplicity in 2024, primarily by consolidating many security platforms into fewer ones that can perform multiple functions. In the data protection landscape, these platforms could be capable of not just protecting data but also continuously locating and classifying it before applying encryption, tokenisation, or any other steps in line with an organisation’s policy.
2. Implement the latest in privacy-enhancing technologies
The growing emphasis on data privacy will naturally lead to a greater focus and adoption of the latest privacy-enhancing technologies (PETs), designed to minimise the amount of personally identifiable data (PID) that businesses need to collect and process. Once implemented, organisations will face less risk of non-compliance with data protection laws and data breaches.
Examples of these technologies include pseudonymisation and anonymisation techniques, which disguise PIDs to prevent them from being linked back to their owner. In addition to PETs, privacy-preserving computation techniques, such as federated learning and differential privacy, are also poised to grow and allow for data analysis without exposing sensitive information.
3. Leverage AI and machine learning for threat detection
Artificial intelligence (AI) and machine learning (ML) have long been used to improve threat detection as they enable rapid analysis of data and identification of patterns and anomalies that can uncover an ongoing phishing attack. By enabling faster and more accurate threat detection, businesses can be more effective at immediately responding to cyber threats.
Not only that, AI and ML can also be fed with historical data and trends to predict potentially new and unknown threats. This predictive capability can assist organisations in staying one step ahead of bad actors and proactively strengthening their cybersecurity posture before an attack occurs.
4. Adopt more advanced encryption techniques
Encryption is a cornerstone of data protection as it has been the most robust defence against unauthorised access and disclosure. As the need for better encryption grows to meet modern demands, how we use and manage it are set to dramatically change in the coming years.
For instance, quantum-resistant encryption algorithms are already on the rise as they are inherently designed for use with quantum computers, which pose a significant threat to existing encryption standards. There is also homomorphic encryption to look out for. As a technique that facilitates performing computations on encrypted data without having to decrypt it first, it offers exciting new possibilities for secure data analysis and processing.
Conclusion
Data protection is a critical concern that will continuously evolve and shape the modern world for years to come. The best practices discussed above highlight the importance of staying ahead of the curve in this aspect of our digital lifestyles, and hopefully, they serve you well in securing your valuable data.
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