Logpoint vs Splunk User Behavior Analytics comparison

Logpoint is a cutting-edge security information and event management (SIEM) solution that is designed to be intuitive and flexible enough to be used by an array of different businesses. It is capable of expanding according to its users' needs. 

Benefits of Logpoint

Some of the benefits of using Logpoint include:

• Unifies data logs: Logpoint creates a single system of classification for collected data. It makes it easy for users to search for and find data, which aids users when they are creating reports or alerts. Users can conserve resources while at the same time seeing a rise in the efficiency of their business operations.

• Intuitive solution design: Logpoint is designed so that anyone can utilize all of its features, even if they are not an expert in network security. Logpoint’s UI is simple enough that users can utilize it without undergoing extensive training. 

• Highly flexible: Logpoint is designed so that users can scale it linearly to accommodate projects that are large and complex. This allows users to expand the scope of their projects according to their needs without worrying that their infrastructure won’t be able to handle the increase in size. The solution’s security features can be deployed both on the cloud and in a physical environment. 

• Simple role-based access security: Logpoint allows administrators to employ Microsoft’s active directory (AD) and a Lightweight Directory Access Protocol to manage user access. These can help administrators protect their systems from being abused or otherwise harmed by bad actors. 

Reviews from Real Users

Logpoint is a security and management solution that stands out among its competitors for a number of reasons. Two major ones are its data gathering and artificial intelligence (AI) capabilities. Logpoint enables users to not only gather the data, but also to maximize both the amount of data that can be gathered and its usefulness. It removes many of the challenges that users may face in data collection. The solution allows users to set rules for collection and then it pulls information from sources that meet the rules that have been set. This data is then broken into manageable segments and ordered. Users can then analyze these ordered segments with ease. Additionally, LogPoint utilizes both machine learning and AI technology. Users gain the ability to protect themselves from and if necessary resolve emerging threats as soon as they arise. The AI sets security parameters for a user’s system. These act as a baseline that are triggered and notify the user if anything deviates from the rules that it set up. 

The chief infrastructure & security officer at a financial services firm writes, “It is a very comprehensive solution for gathering data. It has got a lot of capabilities for collecting logs from different systems. Logs are notoriously difficult to collect because they come in all formats. Logpoint has a very sophisticated mechanism for you to be able to connect to or listen to a system, get the data, and parse it. Logs come in text formats that are not easily parsed because all logs are not the same, but with Logpoint, you can define a policy for collecting the data. You can create a parser very quickly to get the logs into a structured mechanism so that you can analyze them.”

A. Secca., a Cyber Security Analyst at a transportation company, writes, “It is an AI technology because it is using machine learning technology. So far, there is nothing better out there for UEBA in terms of monitoring endpoints and user activity. It is using machine learning language, so it is right at the top. It provides that capability and monitors all of the user’s activities. It devises a baseline and monitors if there is any deviation from the baseline.”

Splunk User Behavior Analytics is a behavior-based threat detection is based on machine learning methodologies that require no signatures or human analysis, enabling multi-entity behavior profiling and peer group analytics for users, devices, service accounts and applications. It detects insider threats and external attacks using out-of-the-box purpose-built that helps organizations find known, unknown and hidden threats, but extensible unsupervised machine learning (ML) algorithms, provides context around the threat via ML driven anomaly correlation and visual mapping of stitched anomalies over various phases of the attack lifecycle (Kill-Chain View). It uses a data science driven approach that produces actionable results with risk ratings and supporting evidence that increases SOC efficiency and supports bi-directional integration with Splunk Enterprise for data ingestion and correlation and with Splunk Enterprise Security for incident scoping, workflow management and automated response. The result is automated, accurate threat and anomaly detection.