XDR Vs EDR: Which is Better?

Denial of Service (DOS), malware, phishing, injection attacks, and others have become a nightmare in a world reliant on computer systems. That’s why cybersecurity professionals are always on the front lines of protecting computer systems from threats. Unfortunately, as thorough as a security system may be, some stealth threats that remain undetected still exist.

There are examples of threats that linger in the cracks of disconnected alert solutions and between security silos, spreading throughout the system quietly with time. At the same time, overburdened cybersecurity professionals unsuccessfully try to stay ahead of threats with their limited and sometimes disjointed resources.

XDR is here to enhance the efforts of cybersecurity analysts.

What Is XDR?

XDR – Extended Detection and Response – is a new threat detection and response strategy designed and optimized to render comprehensive cybersecurity and prevent misuse and unauthorized access to systems. XDR comprises a slew of systems, tools, and data that enhance visibility, analysis, and, importantly, response to threats across clouds, networks, applications, and endpoints.

XDR is a lot more advanced and sophisticated than the Endpoint Detection and Response we’ve traditionally used. XDR takes a comprehensive approach to detecting and responding to the breakdown of security silos. The new system attains and correlates data activity with detections from the servers, cloud workloads, emails, endpoints, and networks across various layers of security.

Consequently, XDR detects threats faster by automating the analysis of the superset of rich data. This allows security analysts to perform investigations much more quickly and efficiently.

The Challenges Security Operations Centers Face And How XDR Could Help

Cybersecurity analysts are professionals who work in security operation centers to negate cyber risk and damage to companies and organizations. As such, they must act expeditiously to threat detection and response. Some of the challenges they have to overcome are:

#1. Alerts Overload

Did you know that a company with 1,000 staff members can generate about 22,000 security events every second, overwhelming the Security Information and Event Management system (SEIM)? That explains why cyber security departments are frequently overwhelmed.

Such a company can generate about 2 million security incidents every day. However, cybersecurity companies are typically underequipped and lacking tools that allow them to correlate and prioritize notifications. Security personnel cannot quickly, efficiently, and effectively process and analyze security alerts.

However, XDR improves this aspect of cybersecurity. The system combines successive low-confidence security alerts/activities into high-confidence events, creating fewer but highly prioritized alerts.

#2. Activity Visibility Gaps

It’s standard for security systems and products to allow analysts to view activities. However, each product uses unique approaches to collecting and presenting valuable data for the task. Additionally, it’s possible to consolidate and interchange data available on different security platforms by integrating the security systems.

That said, the value of the consolidated data is limited in depth and the type of data available. Consequently, analysts are limited in the data they can view and use.

XDR is different because it gathers information and avails all the data to the analysts. The range of data available includes activities from all the security tools, metadata, threat detections, telemetry, and NetFlow.

By combining robust threat detection and powerful analytics, XDR allows viewers to understand the entire context necessary for an attack-centric view of the chain of events across different security layers.

#3. Difficulty Investigating

It can be challenging to identify threats when there are many warnings and logs without clear indicators. Likewise, it’s challenging to map out a threat’s course. All of this makes it difficult o evaluate the threat’s impact on an organization.

Even when resourced and equipped well, conducting investigations has traditionally been a manual and time-consuming process. XDR eliminates the manual process and procedures that afflict threat investigations. XDR comes with an extensive list of tools and data that make traditionally unachievable investigations easy.

A case in point is the root-cause analysis. XDR makes the attack path and timing readily available, including the cloud workloads, networks, servers, emails, and endpoints. As such, the analyst can examine every attack stage and determine the best course of action.

#4. Slow Detection & Response

With the above challenges in mind, it’s easy to appreciate why threats can go far too long before being detected. And when it takes longer to detect threats, it also takes longer to react to them, increasing the risk and severity of attacks.

XDR improves detection rates and reduces the reaction times to threats. Mean-Time-To-Detect (MTTD) and Mean-Time-To-Respond (MTTR) are essential performance metric, and many companies are increasingly tracking and monitoring it. Additionally, organizations continuously monitor the investments and solutions they use in relation to how they influence MTTD and MTTR and lower a company’s business risks.

XDR Vs. EDR: Which System Is Better?

In many ways, XDR is an upgrade in and departure from the traditional methods of detection and response to threats. It shifts from single vector point solutions that Endpoint Detection and Response (EDR) provides. While EDR has been essential to many companies’ cybersecurity, it has a limited breadth of capacity.

Its most significant limitation is it’s only able to identify and respond to threats originating from managed solutions. Consequently, EDR can only discover a limited range of risks with a narrow breadth of what and who is affected. Ultimately, SOC’s have limited capacity and capability to respond effectively.

Additionally, EDR’s scope of Network Traffic Analysis (NTA) systems is restricted to monitored network segments and networks. NTA systems usually generate an enormous amount of logs. Network alerts and other activity data combine to help make sense of the network alerts themselves as well as extract valuable insights.

The Augmentation of Security Information and Event Management (SIEM)

Organizations use SIEMs to collect logs and alerts from their cybersecurity solutions. As such, SIEMs allow organizations to assemble amount of data from a wide variety of sources and create a centralized visual viewpoint. However, this creates an enormous number of alerts.

Consequently, the large number of alerts makes it challenging to filter through them and determine the important ones. Using SEIMs alone, it is challenging to connect and correlate all of the information logs, thereby developing a wider context.

XDR works by gathering and storing deep activity data in a data lake. This structure allows analysts to hunt, sweep, and investigate threats across security layers. Consequently, the systems develop fewer but context-rich alerts for the SIEM solution owing to incorporating expert analytics and AI.

When used this way, XDR complements SIEM solutions instead of replacing the system. Notably, the use of XDR helps to save time while assessing relevant alerts and logs. It helps cybersecurity experts to determine alerts and records that need attention quickly.

Capability Assessment

It’s essential to protect other layers of the system beyond the endpoint. You need two or more layers to implement extended detection and response, including server, emails, workload, network, and endpoint.

XDR collects activity data from several system tiers and collates it into a data lake. All the essential data is availed for fast, efficient, and effective analysis and correlation.

Having the native security stack from one vendor limits the use of different vendor solutions and security stacks. Additionally, limiting the number of vendor solutions improves the level of interaction between and integration of detection response and response capabilities.

Expert Security Analytics Using Purpose-built AI

One of XDR’s greatest strengths is the ability of the system to collect data. Importantly, however, the XDR allows cybersecurity experts to use AI and analytics for faster and better detection. Companies are increasingly applying telemetry collection, which, when used with threat detection, will enable organizations to transform information into insight and action.

Analytics engines that use native, intelligent sensors will be more effective in analyzing security threats than third-party telemetry and solutions alone. Every vendor will have an excellent understanding of their data than data from third parties. With this in mind, consider using XDR solutions purpose-built to take advantage of the vendor’s native stack, enhancing your analysis capacity.

XDR: Single, Integrated, & Automated Platform That Provides Full Visibility

Since you can form logical connections from data supplied from one perspective, XDR solutions make it possible to conduct intelligent investigations. When you generate a graphical, attach-centric timeline, you can get all the following responses:

#1: How did the endpoint become infected?

#2: What’s the attack’s initial point of contact?

#3: What activities were involved in the attack?

#4: What’s the origin of the threat?

#5: How and what means did the threat use to spread?

#6: How many other endpoints were exposed to that particular threat?

In conclusion, XDR solutions enhance the security analysts’ capability while streamlining investigative procedures. These solutions help teams enhance their efficiency by eliminating manual tasks and speeding up processes. It enables analyses and provides perspectives that are impossible to get with traditional cybersecurity systems. Analysts can derive XDR insights from the broader security ecosystem by combining SIEM solutions and security orchestration with automation and response.