Winning In An AI Driven Contextual Security Paradigm
Part ONE of a multiple part series.
In my previous deep-thought article entitled “The Next Era of Cyber Security Capabilities,” I explored the evolution and requirement for “context” in modern cybersecurity products. The critical difference between traditional cybersecurity technologies and contemporary platforms is the use of context and artificial intelligence to make more intelligent and accurate decisions. The new era of cyber takes infinite data points and adds them together to create context, then feeds that context back into the training algorithms, thus gaining compounding value over time. AI is required to process these large data sets to derive context-based answers rapidly, suggesting a future where AI-driven cybersecurity technologies can observe and protect digital realms like never before.
Given this description of a “contextual” cybersecurity future, specific requirements exist for any vendor that wishes to become the dominant player in the emerging contextual security (AI cyber) space. Both technology and usability innovations are required in this new and exciting area of cybersecurity products.
Winners and Losers
In the landscape of contextual cybersecurity, winners and losers among vendors will be determined by the amount of data they can collect, the strength of the context they build, how they integrate with other technologies to collect the data, and if they can innovate new technology capabilities on top of the context set in a way that provides rapid value. Look for these criteria in the vendor you invest in.
Winners: Vendors that embrace AI and machine learning to enhance contextual analysis will come out ahead. Companies that effectively integrate their solutions with broader ecosystems, ensuring seamless data flow and contextual insights across different platforms, are poised to succeed. Those who invest in developing systems that can rapidly adapt to new threats and offer proactive security measures based on rich contextual data will be at the forefront.
Losers: Vendors that fail to move beyond traditional, siloed approaches to cybersecurity will struggle. Companies that are slow to integrate AI and machine learning or do not effectively utilize the increasing availability of data for contextual analysis will fall behind. Vendors that resist evolving their products to work seamlessly in cloud-based, API-driven environments or cannot provide a holistic view of security threats will lose relevance.
Criteria for Contextual Cybersecurity Success
The future of cybersecurity hinges on a strategic blend of context creation and intelligent data handling. These criteria define the capabilities of cutting-edge cybersecurity solutions and shape how they integrate within the broader technology ecosystem. From harnessing advanced AI to ensuring comprehensive data collection, these principles form the cornerstone of a robust and future-proof cybersecurity platform. Specific criteria will determine success:
Breadth and depth of data collection: This refers to the comprehensive gathering of varied data types from multiple sources to create a rich data pool. The breadth refers to the range of data types and sources – encompassing everything from network traffic, user behavior, and application logs in both cloud and SaaS environments. The depth pertains to the level of detail and historical data accumulated, allowing for nuanced analysis. This extensive collection is crucial for AI systems to understand standard patterns and identify anomalies effectively. It enables the construction of a more detailed and accurate contextual landscape, which is crucial for predictive analytics and proactive threat mitigation.
Integrations and data enrichment from external sources: Ensuring that cybersecurity solutions integrate smoothly with various platforms and ecosystems enhances the overall security posture. The additional data enrichment from external sources provides a more robust depth of data, resulting in more accurate and detailed context creation. The data could even come from sources beyond security, including business, human resources, financial, and sales and marketing output.
Feedback loops of context for continuous learning: A network effect is formed when data is turned into context and then fed back into the training system as a new data piece. The compounding effect of this feedback loop creates a system where knowledge grows over time, and data analysis accuracy is self-improving. Whichever technologies understand this concept and can build a system that improves over time will have a distinct advantage in the market. Like compound interest, the sooner they start learning, the sooner they will hit acceptable levels of accuracy. Essentially, contextual cybersecurity is a race against time that must start sooner rather than later.
Ease of use and seamless interoperability: Ensuring that cybersecurity solutions can integrate smoothly for the consumption and usability of results with various platforms and ecosystems enhances the overall security posture. Balancing advanced technology with user experience and usability of output creates a robust and user-friendly solution. Any vendor wanting to dominate in this emerging market must surface value quickly, in the appropriate formats, and make it easy to use for several different user personas. This is NOT going to be an easy task.
The Enterprise Path To Glory - What This Means For The CISO!
While the path to contextual cybersecurity glory seems clear, it is anything but. Vendors that understand the success criteria listed above and the vision of the future will undoubtedly have a leg up on the rest of the market. Still, like anything in business, execution is always more complex than ideation. The devil is indeed in the details.
We are still in the early days. Enterprise cybersecurity leaders must understand the requirements for future success but be careful not to over-index on this vision too quickly. It’s very easy to get out in front of the reality of what products are actually capable of, resulting in a situation where you are less secure than before you rallied behind the innovations. Don’t buy too much into the hype; instead, be pragmatic and pay attention to how solutions such as these can fit into your cybersecurity program today and augment what you are already achieving. As they say in comedy, timing is everything.
Coming soon: A new deep-thought piece on the cybersecurity vendors and platforms positioned well to succeed and the submarkets they will come to dominate. Stay tuned to The Cyber Why for more!
Could not agree more with the Winners and Losers and Criteria for Success lists. I feel like Copilot for Security is *very* well placed in this context. If you're an Azure shop, it's pretty much zero additional data exposure, we can talk to it in natural language, and it will integrate with other big dogs like Splunk.