User & Entity Behaviour Analytics

UEBA technologies employ analytics to construct standard profiles and behaviours for users and entities (servers, routers) in an Enterprise firm over a period. This is referred to as “baselining”. Activity that differs from these standard baselines is flagged as suspicious by UEBA technology and analytics applied to these anomalies helps in the discovery of possible risks and security incidents.

While buying UEBA Solution following points must be considered –

Data Sources – The UEBA solution must support various data sources.

A SIEM is a data gathering point for a wide range of security data from users’ directories, logs, and other security solutions. Over other data sources, SIEM information has the advantage of being readily available to put into a security solution.

Endpoint data is collected by a smaller number of security vendors. Most collect data directly or from a SIEM via an existing endpoint. User behaviour related to application, network, and cloud activity can be found in endpoint data. It is an important data source.

For security analysis, two more data sources are critical. The log data from major enterprise software like SAP and Oracle. Gathering this information will provide more insight into cyberattacks on organizational operations and financial information.

Machine Learning and Behavioral Analysis

A security analytics solution’s purpose is to swiftly detect threats across the company, particularly those that are often undetected by conventional methods. Behavioural analytics establishes a distinct baseline for each company’s entity. These activities should be linked to the participants like users/accounts, machines, apps, data, and other digital assets are examples of entities. Probabilistic approaches can measure how irregular an occurrence is by computing an appropriate risk score as entities engage in anomalous activities. So, machine learning algorithms play a key role in identifying cyber threats. Machine learning also defines the baseline for behaviour and does behavioural analysis. Hence, companies should look for a UEBA vendors who have extremely efficient and accurate machine learning algorithms.

Incident Response and Investigations

When in incident response, the purpose of UEBA is to clearly identify and present a threat. UEBA will give a security team actionable information about the issue so that it can be prevented before data is compromised. To respond to an incident the UEBA solution should clearly identify and present a threat. It should include possible responses to the incident. So, firms should look for vendors who present incident information with good quality information and visual graphs. The companies should also assess what various investigation and incident response options are provided by the vendors.

Ease of Use

Complex user interfaces have hampered security products in the past. The majority fails to show where the biggest risk is in a comprehensive manner and what the nature of that risk is. Typically, tools’ dashboards will display the change over time, some events, such as a potentially dangerous IP address or malware fingerprint. These tools require rigorous training to master. Hence, companies should look for UEBA solution with user-friendly interface and customization options.

Performance and Scalability

The UEBA solution should be scalable. Security analysis will be done on the firm’s all endpoints across different sources like customers and vendors.  This results in billions of processes per month utilizing heavy storage. The UEBA solution you must be designed to cope up this scale.  In addition, the UEBA solution must be able to scale up down quickly and handle data in real-time as per business requirements. 

Use Cases

The major use case for UEBA solutions is the identification of multiple types of threats, which is accomplished through analysis of frequently correlated user and other entity behaviour. Monitoring for unauthorized data access, suspect privileged user behaviours, and generally improving detection processes are examples of use cases.  However, non-IT and non-security data sources are frequently required like analytics models detecting fraud. So, these analytical models learn from uses case-based data. Hence, better the use case increases threat detection accuracy. So, companies should look for UEBA solutions with rich and quality uses cases and analytical models.

Cost and Support

It’s important to look into the type of assistance that a particular vendor offers. In any case, comprehensive technical support is an optional extra that could dramatically increase implementation expenses. Due to the fact that UEBA products have an expiration policy, which means the vendor will no longer support them, the cost and number of software upgrades must be considered. The cost of UEBA varies based on the features, power of analytics, size and capabilities of the network. What is the maximum amount of money that a company is willing to spend? Is the business concerned about ROI? The second step after selecting a UEBA product is to implement and support it. To be effective, UEBA must be administered by dedicated trained workers or added to the responsibilities of professional staff. There are disparities in terms of costs and levels of service assistance.