Monday, October 15

Improve Security by Thinking Beyond the Security Realm

It used to be that dairy farmers relied on whatever was growing in the area to feed their cattle. They filled the trough with vegetation grown right on the farm. They probably relied heavily on whatever grasses grew naturally and perhaps added some high-value grains like barley and corn. Today, with better technology and knowledge, dairy farmers work with nutritionists to develop a personalized concentrate of carbohydrates, proteins, fats, minerals, and vitamins that gets added to the natural feed. The result is much healthier cattle and more predictable growth.

We’re going through a similar enlightenment in the security space. To get the best results, we need to fill the trough that our Machine Learning will eat from with high-value data feeds from our existing security products (whatever happens to be growing in the area) but also (and more precisely for this discussion) from beyond what we typically consider security products to be.

In this post to the Oracle Security blog, I make the case that "we shouldn’t limit our security data to what has traditionally been in-scope for security discussions" and how understanding Application Topology (and feeding that knowledge into the security trough) can help reduce risk and improve security.

Click to read the full article: Improve Security by Thinking Beyond the Security Realm

Tuesday, September 18

Convergence is the Key to Future-Proofing Security

I published a new article today on the Oracle Security blog that looks at the benefits of convergence in the security space as the IT landscape grows more disparate and distributed.

Security professionals have too many overlapping products under management and it's challenging to get quick and complete answers across hybrid, distributed environments. It's challenging to fully automate detection and response. There is too much confusion about where to get answers, not enough talent to cover the skills requirement, and significant hesitation to put the right solutions in place because there's already been so much investment.

Here's are a couple of excerpts:
Here’s the good news: Security solutions are evolving toward cloud, toward built-in intelligence via Machine Learning, and toward unified, integrated-by-design platforms. This approach eliminates the issues of product overlap because each component is designed to leverage the others. It reduces the burden related to maintaining skills because fewer skills are needed and the system is more autonomous. And, it promotes immediate and automated response as opposed to indecision. While there may not be a single platform to replace all 50 or 100 of your disparate security products today, platforms are emerging that can address core security functions while simplifying ownership and providing open integration points to seamlessly share security intelligence across functions.
 ...
 Forward-looking security platforms will leverage hybrid cloud architecture to address hybrid cloud environments. They’re autonomous systems that operate without relying on human maintenance, patching, and monitoring. They leverage risk intelligence from across the numerous available sources. And then they rationalize that data and use Machine Learning to generate better security intelligence and feed that improved intelligence back to the decision points. And they leverage built-in integration points and orchestration functionality to automate response when appropriate.
Click to read the full article: Convergence is the Key to Future-Proofing Security

Tuesday, January 30

New World, New Rules: Securing the Future State

I published an article today on the Oracle Cloud Security blog that takes a look at how approaches to information security must adapt to address the needs of the future state (of IT). For some organizations, it's really the current state. But, I like the term future state because it's inclusive of more than just cloud or hybrid cloud. It's the universe of Information Technology the way it will be in 5-10 years. It includes the changes in user behavior, infrastructure, IT buying, regulations, business evolution, consumerization, and many other factors that are all evolving simultaneously.

As we move toward that new world, our approach to security must adapt. Humans chasing down anomalies by searching through logs is an approach that will not scale and will not suffice. I included a reference in the article to a book called Afterlife. In it, the protagonist, FBI Agent Will Brody says "If you never change tactics, you lose the moment the enemy changes theirs." It's a fitting quote. Not only must we adapt to survive, we need to deploy IT on a platform that's designed for constant change, for massive scale, for deep analytics, and for autonomous security. New World, New Rules.

Here are a few excerpts:
Our environment is transforming rapidly. The assets we're protecting today look very different than they did just a few years ago. In addition to owned data centers, our workloads are being spread across multiple cloud platforms and services. Users are more mobile than ever. And we don’t have control over the networks, devices, or applications where our data is being accessed. It’s a vastly distributed environment where there’s no single, connected, and controlled network. Line-of-Business managers purchase compute power and SaaS applications with minimal initial investment and no oversight. And end-users access company data via consumer-oriented services from their personal devices. It's grown increasingly difficult to tell where company data resides, who is using it, and ultimately where new risks are emerging. This transformation is on-going and the threats we’re facing are morphing and evolving to take advantage of the inherent lack of visibility.
Here's the good news: The technologies that have exacerbated the problem can also be used to address it. On-premises SIEM solutions based on appliance technology may not have the reach required to address today's IT landscape. But, an integrated SIEM+UEBA designed from the ground up to run as a cloud service and to address the massively distributed hybrid cloud environment can leverage technologies like machine learning and threat intelligence to provide the visibility and intelligence that is so urgently needed.
Machine Learning (ML) mitigates the complexity of understanding what's actually happening and of sifting through massive amounts of activity that may otherwise appear to humans as normal. Modern attacks leverage distributed compute power and ML-based intelligence. So, countering those attacks requires a security solution with equal amounts of intelligence and compute power. As Larry Ellison recently said, "It can't be our people versus their computers. We're going to lose that war. It's got to be our computers versus their computers."
Click to read the full article: New World, New Rules: Securing the Future State.