The latest “Cost of a Data Breach Report” from IBM reveals that the average cost of a data breach has reached a staggering $4.5 million per incident globally. While the direct impact of a breach includes stolen data, the consequences can extend far beyond that. Lost profits and damage to corporate reputation can have a lasting effect on businesses, eroding customers’ trust and leading to declining stock prices for public companies. To mitigate these risks, organizations need to undergo a paradigm shift in their security strategies.
Traditionally, the focus of security efforts has been on building defenses around the network and keeping malicious actors out. However, this approach has proven insufficient, as it fails to address vulnerabilities associated with distributed workforces and third-party access to enterprise assets. Instead, organizations should shift their focus to building security around the data itself.
This new security model involves embedding granular security controls around digital assets, ensuring that they are used only as intended. These controls travel with the data, regardless of whether it is shared or stored inside or outside the enterprise. By securing data outside the network perimeter, organizations can retain visibility and control over their sensitive assets, even when sharing information with third-party collaborators. This approach allows organizations to secure their supply chain without impeding growth, while also proactively mitigating the impact of future breaches.
To successfully implement this paradigm shift, security professionals can follow five key steps:
1. Communicate the need for change to executive leaders: Before transitioning to a data-oriented model, it is crucial to gain buy-in from the executive team. Highlight recent high-profile breaches and their financial and reputational consequences. Emphasize the benefits of the shift, such as improved compliance, to resonate with non-technical stakeholders.
2. Know and classify your data: Identify the most valuable data and classify it based on its purpose, format, location, and users. Understanding the different types of data within the organization is essential for developing effective security policies.
3. Develop policies for continuous data protection: Consider the lifecycle of the data and the varying levels of risk associated with different groups of data. Involve real users of the data to create policies that are practical and usable.
4. Automate data protection: Automation is critical in data security to minimize human error and oversights. Automate processes such as data classification based on user or content to ensure consistent protection.
5. Solicit feedback and prioritize usability: Involve employees outside the security team to gather feedback on security measures. This helps to identify areas where flexibility is needed and ensures that security measures do not hinder workflow processes.
By implementing these steps and shifting the focus to data-centric security, organizations can enhance their security practices and reduce the impact of breaches. This paradigm shift allows companies to protect their most critical assets and render breaches inconsequential, ultimately safeguarding their reputation and financial stability. In a future where breaches are no longer a significant concern, organizations can operate with confidence knowing that their data remains safe even in the face of potential infiltrations.