ExtraHop Reveal(x) vs Splunk User Behavior Analytics comparison

ExtraHop Reveal(x) is a highly effective network traffic analysis (NTA) solution that leverages a cloud-native architecture to empower organizations to overcome a world filled with increasingly sophisticated threats. It identifies 25% more threats than its competitors. Additionally, organizations that employ Reveal(x) say they resolve issues 77% percent faster than they would if they were using other similar solutions.

ExtraHop Reveal(x) Benefits

Some of the ways that organizations can benefit by choosing to deploy ExtraHop Reveal(x) include:

• Total network visibility. Reveal(x) gives users the ability to view every component of their network and devices connected to it in real time. It can automatically recognize and classify the devices that are communicating across an organization’s network. These devices are scanned by powerful decryption software that reveals hidden threats and the details of critical transactions without compromising privacy or compliance rules. Organizations are given full East-West visibility across both physical data centers and cloud environments. Threats that are on the periphery are brought to the attention of the administrators tasked with watching out for them.

• Identify threats in real time. Reveal(x) extracts more than 5,000 features from the L2-L7 security layers at any given time, feeds them into its machine learning engine, and presents them to its rule-based detection feature. These features make it possible for the solution to identify the most severe threats. Users can conduct a threat triage and address the threats that their system detects in the order of severity that these threats represent.

• Ease of use. Users of Reveal(x) can easily make full use of its event remediation features without expending long periods of time learning them. Its workflows are designed so that administrators can go from a security event to the cause of the event in only a couple of clicks. What would normally take hours can be completed in moments.

ExtraHop Reveal(x) Features

• Integration suite. Reveal(x) enables users to utilize a robust suite of integrations. If users feel they are missing important capabilities, they can bolster their security feature toolbox with those offered by third-party solutions. Phantom, Splunk, and Palo Alto are three examples of solutions that Reveal(x) enables users to connect to in order to fill in a gap in their security capabilities.

• Automated inventory. Reveal(x) automatically creates a detailed inventory of all of the devices that it discovers and classifies. This keeps an always up-to-date record of all of the devices that are communicating in a given network.
  
  
• Machine learning. Reveal(x)’s real-time application analytics is driven by a machine learning engine. It detects anomalies in an organization’s network traffic, thus enabling users to keep ahead of any and all threats while reducing the number of false positives that administrators have to sort through.

Reviews from Real Users

ExtraHop Reveal(x) is a solution that stands out when compared to many other similar solutions. Two major advantages that it offers are its versatility and its ability to quickly identify the root cause of an application’s issues.

John B., the senior monitoring engineer at a financial services firm, says, “It's useful for different teams in our organization. The cybersecurity team uses it because it has got great analytics for anomaly detection, malware detection, and ransomware. It's used by the networking people because it's great to be able to get the three-way handshake between systems to see how your network is doing. The microservices for DNS use it because they like to be able to see how their DNS services are operating and how many DNS requests are being rejected, denied, or dropped. Application people love it because it fully decrypts their traffic.

Henry S., a systems engineer at LifePoint Health, writes, "When there are performance issues with an HTTP app, ExtraHop enables us to identify the causes within a few minutes. We can see what transactions are being impacted by something that may be happening within the server environment."

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.