SIEM is a solution that assists businesses in detecting, assessing, and mitigating security risks before they affect regular operations. The goal of a security information and event management (SIEM) solution is to remove attackers from a system by collecting data from throughout the firm, normalizing it so it can be searched, analyzing it for anomalies, and then investigating events and fixing issues. The use of distributed architecture by businesses is at an all-time high. When an architecture's design is intricate, there are more weak points that a malicious actor can exploit. The possibility of a cyber attack on the company is so increased.

Today's cyber security technological evolution milestones in the context of effective detection and response are the endpoint detection and response (EDR), Manage Detection and Response (MDR), and Network Detection and Response (NDR). However, these all solutions are running independently and missing the correlated high level processed alert to which Extended Detection and Response (XDR) is a solution that emerged, rather than adding another tool, XDR aims to change this security landscape and enable a more compelling activity of the security stack. What problem does XDR solve? Attackers often target endpoints, but they also target other layers of the IT domain in the corporate network, such as email servers and cloud systems, and they may bounce between layers or hide in the interface between them to evade detection. XDR solves both problems at once.

The SIEM, or security information and event management console, has been a staple for security teams for more than a decade. It's the single pane of glass that shows events, alerts, logs, and other information that can be used to find a breach. Despite its near ubiquity, I've long been a SIEM critic and believe the tool is long past its prime. This is certainly not the consensus; I've been criticized in the past for taking this stance. While robust passwords help you secure your valuable online accounts, hardware-based two-factor authentication takes that security to the next level.

Damian Ehrlicher is a Board Member of several emerging technology funds and companies and the CEO of Protected IT. In today's day and age of machine learning (ML) and artificial intelligence (AI), the number of organizations leveraging these technological advances to mitigate risk is growing quickly. As fast as the cybersecurity community can develop new solutions predicated on these technologies, malicious actors are developing tools leveraging these technologies as well. In days past, automation in the NOC/SOC was used to deploy new services or run a set of standard tests when a specific ticket came through the system. Now ticket enrichment is only part of the solution because software automation has made its way into the cybersecurity space.

What is "Cyber Intelligence" in relation to SecOps? Are we talking about a SIEM (Security Information and Event Management) that has intelligence? Although that is necessary, it is not sufficient. Many people talk about Artificial Intelligence these days where a SIEM learns more about threats in the environment and then makes decisions based on them. This is an intriguing component and our SIEMs are growing in that direction.

Some attacks may still slip "under the radar" though, which is why tools that leverage machine-learning, like User and Entity Behavior Analytics (UEBA), are an important support to your SIEM as they will detect more unusual threats as well as greatly increase the overall fidelity of your security alerts. SIEM and UEBA are further supported by threat hunting tools that enable your hunt teams to track down any other threats that may still be lurking in your system. All three approaches are important to your threat detection and response ecosystem. Micro Focus is a global software company with 40 years of experience in delivering and supporting enterprise software solutions that help customers innovate faster with lower risk. Our portfolio enables our 20,000 customers to build, operate, and secure the applications and IT systems that meet the challenges of change.

There is a pernicious myth floating around. It's that rule-based Security Information and Event Management (SIEM) is old technology, and is no longer worth using today. It's that modern attacks can bypass rule-based SIEMs. This is partly true, but mostly false. There are large, older companies out there that don't use SIEMs to defend their data, and they do so at their own risk.

SureLog SIEM is a security platform which differs from many SIEM products. The main difference is; correlation engine which you can develop your own logic with a High-Level Domain-specific Language. There is no restriction in the logic because you can develop your logic in JAVA including Machine learning, statistical methods and artificial intelligence. SureLog is ready for the fallowing ML libraries also. SureLog has a correlation engine and has a feature called Rule As a Code which is Rule Code.

There are many SIEM solutions available. Some of those ML/AI tools available are using pure statistics for outlier detection apart from current hot topic ML, AI algorithms. What is tactical SIEM? if you are spending 80 percent of your time within a SIEM tool doing alert review and analysis, then you are on the right track. If you are an organization that is instead focusing heavily on collecting more data sources, applying patches, or running compliance reports, then your SIEM implementation may not be tactical. So correlation/alert is the heart of SIEM.

Although security information and event management (SIEM) has been around for more than a decade, the solution continues to evolve. But too many enterprises still don't know which security use cases SIEM can take on, how it can capture and leverage data -- structured and unstructured, internal and external -- or how to effectively implement a SIEM solution. Security talent remains in short supply, while point solutions have become all too common. Defenders need a SIEM solution to detect threats in the extended environment, artificial intelligence (AI) to identify connections behind suspicious activity, and automated processes to rapidly shut down attacks. Taking a step back to define the phrase, what is SIEM?