SIEM (Security Information and Event Management) systems have a reputation for being expensive. And that’s generally correct – they can cost hundreds of thousands per year or have huge upfront costs. But why is that? There are several main reasons: All of this is changing. According to Gartner, SIEMs are going to the mid-market and these things don’t hold true there.
The number of cyberattacks has increased five-fold after COVID-19, as the pandemic brought new opportunities to cybercriminals. At this rate, cybersecurity threats are estimated to cost the world US $6 trillion a year by 2021. Since remote working became “the new normal”, it also became a growing gateway to new forms of data theft and as a result, companies face significantly increased risk of cyber-attacks and data breaches.
Alert fatigue is a well-known phenomenon with security products – the security team gets a lot of alerts (from the SIEM, for example), it tries to triage and act upon all of them, but at some point, they are so many and so few of them are actual threats, that the security team just ignores them. And that leads to both overworked security teams and an increased risk for missing an actual threat. Why is that happening? It’s hard to tweak a system right, no matter how flexible it is.
SIEM stands for Security information and event management. This technology has existed since the late 1990s. Traditional SIEM has been joined by a broad use log management technology that focuses on collecting various types of logs and events for different purposes, such as: SIEM vendors usually provide different combinations of functionalities to offer the benefits listed above.
The Sarbanes-Oxley Act (SOX) establishes requirements for the integrity of the source data used in financial transactions and reporting. In particular, auditors are looking at regulated data residing in databases connected to enterprise applications. To prove the integrity of financial data, companies must extend audit processes to the financial information stored within corporate databases.
