But there was a question that popped up a few times that indicates an interesting trend in the market: “A SIEM? Isn’t it old technology?”. No, it is not. It may be an old concept, but definitely not “old technology”.
Look at these two pictures below? What do they show?
Both show cars. But can we say the Tesla is “old technology”? Notice that the basic idea behind both is essentially the same: Transportation. But this, and the fact they have four wheels, is probably the only thing in common. This is the same for the many SIEMs we’ve seen in the market in twenty or so many years.
Here is the barebones concept of a SIEM:
How this is accomplished, as well as the scale of things, have changed dramatically since ArcSight, Intellitactics and netforensics days. Some of the main changes:
- Architecture. Old SIEMs were traditional software stacks running on relational databases and with big and complex fat clients for UI. Compare this with the modern, big data powered SaaS systems with sleek web interfaces. Wow!
- Use cases. What were we doing with the SIEMs in the past? Some reports, such as “top 10 failed connection attempts” or some other compliance driven report. Many SIEMs had been deployed as an answer to SOX, HIPAA and PCI DSS requirements. Now, most SIEMs are used for threat detection. Reporting, although still a thing, is far less important than the ability to find the needle in the haystack and provide an alert about it.
- Volume. SIEM sizing used to be a few EPS, Gigabytes exercise. With the need to monitor chatty sources such as EDR, NDR and cloud applications the measures are orders of magnitude higher. This changes the game in terms of architecture (cloud is the new normal) and also drive the need for better analytics; we can’t handle the old false positive rates with the current base rates of events.
- Threats. It was so easy to detect threats in the past. It was common to find single events that could be used to detect malicious actions. But attacks have evolved to a point where multiple events may be assessed, in isolation and together as a pattern, to determine the existence of malicious intent.
- Analytics. Driven by the changes to threats, volume and use cases, the analytics capabilities of SIEM have also changed in a huge manner. While old SIEMs would give us some regex capabilities and simple AND/OR correlation, modern solutions will do that and far, far more. Enriched data is analyzed with modern statistics and ML algorithms, providing a way to identify the stealthiest threat actions.
With all that in mind, does it still make sense to call these new Teslas of threat detection a “SIEM”? Well, if we still call a Tesla a car, why not keep the SIEM name?
However, differentiating between the old rusty SQL-based tool and the advanced analytics SaaS tools of modern days is also important. In my previous life as an analyst I would frequently laugh at the “Next Gen” fads created by vendors trying to differentiate. But I also have to say it was useful to provide a distinction between the old Firewall and what we now call NGFW. People know the implied difference in capabilities when we say NGFW. With that in mind, I believe saying NG-SIEM is not really a bad thing, if you consider all those differences I mentioned before. Sorry Gartner, I did it! :-)
So, old SIEM dead, long live the NG-SIEM? No, I don’t think we need to do that. But in conversations where you need to highlight the newer capabilities and more modern architecture, it’s certainly worth throwing the NG there.
Tesla owners can’t stop talking about how exciting their cars are. For us, cybersecurity nerds, deploying and using a Next-gen SIEM gives a similar thrill.