Why SureLog is the Right SIEM Solution for you?

SIEM functions based not just on its correlation rules but on the data you feed it. Feeding your SIEM security-related data results in more accurate alerts.

Currently, most of the SIEM products support hundreds of log formats. If there is a log format that is not supported, there is an API for custom log parser. SureLog has nearly 500+ supported device.

SIEM use cases or rules are the %80 of the value of the product. Check the predefined rule list for the product and also check are there any restrictions. A Next-Gen SIEM correlation engine will be very helpful to analysts indeed. Not all SIEM correlation rules, use cases are created equal and it is hard to find a SIEM that supports both core, advanced and intelligent use cases at an affordable price.

All the SIEM products have correlation but not all SIEM solutions are created equal. Detailed analysis required to understand the difference of correlation capabilities. For example, most of the SIEM solutions have watchlist or list management feature, but only some them and SureLog has multidimensional list management capability in correlation. Some solutions like SureLog update multiple lists, sets at the same time while others have not.

Correlation and detection methods and correlation features diversity are important like detecting what never seen before and many others. SureLog can play a huge role in making analysts’ jobs easier with many modern detection and correlation features like never seen before type of rules.

Almost every company needs a solution for protecting its sensitive data and detecting suspicious activity in real time. Besides, when an incident occurs, companies want to be able to provide digital evidence in the courtroom. Integrity also critical. This is usually achieved by using integrity mechanisms, such as running hash checks on blocks of stored log data. Historical log data must be secured either with a checksum in the form of a popular hash — MD5, SHA1, SHA2, etc. — or with a digital signature.

Easily aggregate and search logs within a single platform is critical.

The latest study by the Ponemon Institute on behalf of IBM found that the average time required to identify a data breach is currently 197 days. So having logs under hands at least 197 days is a good plus and makes everything easy for detection and forensic analysis. It is achieved by live search capability. Disk usage for live search is the most critical parameter. Every SIEM solution has its technology with advantages and disadvantages for live search.

Real-Time monitoring and dashboards permits visibility at the desired level via security-based, pre-defined and customizable analysis.

In addition, you can create real time and easy reports by preparing dashboards and widgets which are appropriate for your new ad hoc requirements.

The SureLog application features dashboards on various security topics. Dashboards deliver monitoring and reporting metrics to track the state of security throughout the network. These are simple to configure and user friendly, while allowing users to read a summary of existing network infrastructure data using graphs and tables.

Threats are dynamic and attack vectors change constantly. Respond quickly and minimize damage by using the rich external context enabled by threat intelligence. Immediately know about dangerous IP addresses, files, processes, and other risks in your environment.

SureLog combines multiple threat intelligence feeds and generates alerts for the benefit of the security team. SureLog uses this data to reduce false-positives, detect hidden threats, and prioritize your most concerning alarms.

Regulatory compliance is necessary. SIEM will help to save time and ensure compliance with predefined reports. Creating a productive SIEM environment requires plenty of predefined reports you need on a daily, weekly or monthly basis and also easy to create reporting infrastructure.

SureLog has more than 1400 predefined reports and very easy and fast reporting infrastructure.

Incident response is an action that SIEM takes in response to suspicious activity or an attack. Active response actions include the Block IP active response, the Disable Networking active response, the Log off User active response, the Kill Process active response and so on. SureLog also supports to execute any executable file as a response with parameters from detection rules.

Machine learning in SIEM takes cybersecurity rules and data to help facilitate security analytics. As a result, it can reduce the effort or time spent on rote tasks or even more sophisticated duties. With the right configurations, machine learning can actually make decisions based on the data it receives and change its behavior accordingly. SureLog has many ML models. Some of the ML models used by SureLog

• Detecting tools used by cyber criminals
• Hunting critical process masquerade
• Hunting malware and viruses by detecting random strings
• Domain generation algorithm (DGA) detection
• Profiling user and entity behaviour

The performance analyses of SIEM products are very important in terms of evaluation.

The running performance of SIEM products, the resources which they require (CPU, RAM, DISK) and how they will show performance in the EPS value needed is very important. There are two kind of evaluation parameters:

• Limits and recommendations
• Requirements