There are five things CISOs should do to make operational data more valuable for their security leadership approach.
Leaders in enterprise security have a lot on their shoulders. You are required to manage security programmes pro-actively, regularly monitor outcomes and progress, and provide thorough reports on the state of corporate security to both business and technical stakeholders. You are also expected to pinpoint areas that require improvement. While doing all of this, the enterprise’s business continuity is greatly facilitated.
However, most CISOs are still operating in the dark while having such a broad range of duties, which literally vary from developing strategy to supervising daily operations. To inform their planning, decision-making, and governance, they continue to use outdated, offline data. It might take weeks to receive an answer to a crucial inquiry such as “How prepared are we against ransomware?” or “Is my security policy actually being enforced?” And immediately after being given, responses are frequently out of date.
Building a security data backbone allows security executives to assess and communicate the value of their security programmes more effectively while also removing the overhead associated with data ingestion. As we developed SeeMetrics over the last three years, we accumulated a tonne of information, experiences, and horror tales on how CISOs go about creating a reliable security data backbone.
Establish a lone source of truth
The raw data that comes from the enormous variety of distributed systems that make up your security stack serves as the starting point. The biggest difficulty in this situation is transferring data from cloud and on-premises sources to a single place. The objective is to establish a trustworthy, one source of reality—one location for all security data.
Players like AWS and Snowflake have introduced security data lake programmes in recent months. Unstructured and structured cybersecurity data may be compiled in a security data lake, which can then be used to manage and organise information coming from the stack. However, there are several other procedures that must be completed in order for a security data lake to produce insights that management can employ.
Data normalisation
Therefore, you have centralised your operational data. The issue is that various security solutions make use of various data structures and lingo. Contextual knowledge of each of the security stack’s individual products is essential for normalising such a large number of different security data. You must enlist a variety of security Subject Matter Experts (SMEs) to collaborate with your analytics teams in order to do this. These teams must collaborate to “translate” data into a common language for comparison with similar metrics across other systems because each product’s data structure is unique and comprises hundreds of variants.
Construct meaningful metrics
It’s time to get insights once the data has been normalised. However, metrics based on best practises, KPIs, and other measurements give rise to insights. What exactly should be measured, and how? Complex metric ROI is sometimes difficult to defend. These frequently result in Excel wish lists that are too extensive and ineffective to be of any use. Finding a balance between data that we can get from our stack and metrics that help construct a reasonable story from a business viewpoint is the key in this situation.
Observe the trends
Even the most important indicators should be analysed in light of the dynamic and ever-changing business continuum. For instance, it’s crucial to understand the current number of major vulnerabilities, but it’s even more crucial to understand whether there are more now than there were one month ago. A crucial tool for supporting quarterly or yearly roadmaps, procurement, staffing, or training suggestions is the capacity to show trends. Additionally, it allows for improved attention and resource allocation across BUs and risk regions.
Transform security to be data-driven
You’ve freed up a tonne of security SMEs so they can concentrate on improving security rather than consuming data. You’ve also given yourself more control by establishing a platform for data-driven security decision making. Now you’ll be able to tell whether performance is meeting or exceeding thresholds. This implies that resource-intensive jobs may be managed more skillfully. It also implies that when the time comes to approach the Board and request extra funding, these requests may be connected to existing and real indicators simply and unambiguously.
Conclusion
It’s not that the knowledge you require to guide your security leadership doesn’t already exist. Yes, it does. It just stays submerged in operations. The disadvantages of security tool sprawl are mitigated via a security data backbone. The development and upkeep of a data-driven security decision making platform gives CISOs a fresh, multifaceted perspective. Security leadership can quickly convey progress to organisational leaders, link benchmarks to reality, and implement rules in a proactive manner with constant access to coherent and complete security metrics and trends.
Your security data backbone’s coherent metrics and insights may help you see the big picture, prove your point, and guarantee that your entire organisation is safer and more effective.
