Exabeam, the security analytics, and automation company announces Exabeam Alert Triage, a new cloud-native application that will help security analysts confidently wrangle the overwhelming number of alerts coming at them each day from a myriad of other third-party vendor tools.

Included as a new integrated application for all cloud customers using Exabeam advanced analytics and Exabeam case manager, Alert Triage enriches alerts with context and presents them in a single screen so analysts can make faster decisions about which alerts to escalate or dismiss. It also ensures analysts don’t miss the critical alerts that require escalation to prevent breaches.

Receiving security alerts

Analysts receive thousands of security alerts a day spread across disparate tools. Unable to keep up with the volume, they must ignore a significant number of them, which leaves their organisations vulnerable to threats,” said Adam Geller, chief product officer at Exabeam. “We developed the Alert Triage application to provide automation throughout the triage workflow so security analysts can be freed up to focus on what matters most -- fortifying their organisation's cybersecurity defences to prevent breaches.”

Analysts receive thousands of security alerts a day spread across disparate tools"

We’ve had great success running Alert Triage in its beta version. At first, watching so many alerts get centralised into a single screen was somewhat unbelievable, but Exabeam has done it,” said Zane Gittins, IT security specialist at Meissner. “It’s been refreshing to not have to go from app to app to look at different alerts and it absolutely reduces the time it takes to triage them.”

Traditional triage workflows

Security personnel say they are only able to investigate 45% of the daily alerts they receive, according to research from the Ponemon Institute. The report surveyed 596 IT and security practitioners and also found that 33% of alerts in traditional SIEMs are false positives.

The traditional triage process requires analysts to first determine what the alert is for (users or entities), gather the right contextual information (positions, locations, sources, etc.), and then sift through logs to determine the priority of the alert. Next, an analyst must decide whether or not to escalate it for further review. Blending traditional triage workflows with context generated from machine learning-based analytics, Alert Triage does this time-consuming and tedious work automatically. It categorises, aggregates, and enriches alerts with contextual data including host, IP, severity of alerts, related behavioural anomalies, and overall risk scores of associated users and entities.

Incident response team

The ability to categorise alerts allows managers to create and assign channels to team members

From the security alert, analysts can easily navigate to an associated user or entity timeline to understand what happened before and after the alert was triggered.

Armed with context to understand the scope of the security alert, analysts can rapidly and confidently dismiss or escalate the alert to the incident response team.

Alert Triage benefits include:

  • Visibility - Centralising the alert triage process and organising an analyst's triage efforts enables analysts to review alerts faster. Visibility into all of the alerts that security tools have triggered in an organisation minimises the likelihood that an alert is missed or overlooked.
  • Focus - The ability to categorise alerts allows managers to create and assign channels to team members. A channel helps focus an analyst’s attention on a specific type of alert and allows them to develop subject matter expertise.
  • Productivity - An analyst can triage alerts in aggregate batches, which boosts their productivity. Greater productivity means analysts are able to review a higher percentage of incoming alerts and reduce the possibility that an alert will go unreviewed and lead to a breach.

Latest security incidents

"When we look at the latest security incidents such as the SolarWinds or Microsoft Exchange attacks, more likely than not, the impacted organisations had at least one security alert generated about the threats from one of their third-party security vendor tools,” said Gorka Sadowski, chief strategy officer at Exabeam.

Unfortunately, that alert was likely drowned in all of the other false positive alerts and had to be discarded. Exabeam helps our customers spend time on the alerts that really matter."

Share with LinkedIn Share with Twitter Share with Facebook Share with Facebook
Download PDF version Download PDF version

In case you missed it

Panasonic AI-driven cameras empower an expanding vision of new uses
Panasonic AI-driven cameras empower an expanding vision of new uses

Imagine a world where video cameras are not just watching and reporting for security, but have an even wider positive impact on our lives. Imagine that cameras control street and building lights, as people come and go, that traffic jams are predicted and vehicles are automatically rerouted, and more tills are opened, just before a queue starts to form. Cameras with AI capabilities Cameras in stores can show us how we might look in the latest outfit as we browse. That’s the vision from Panasonic about current and future uses for their cameras that provide artificial intelligence (AI) capabilities at the edge. Panasonic feels that these types of intelligent camera applications are also the basis for automation and introduction of Industry 4.0, in which processes are automated, monitored and controlled by AI-driven systems. 4K network security cameras The company’s i-PRO AI-capable camera line can install and run up to three AI-driven video analytic applications Panasonic’s 4K network security cameras have built-in AI capabilities suitable for this next generation of intelligent applications in business and society. The company’s i-PRO AI-capable camera line can install and run up to three AI-driven video analytic applications. The AI engine is directly embedded into the camera, thus reducing costs and Panasonic’s image quality ensures the accuracy of the analytics outcome. FacePRO facial recognition technology Panasonic began advancing AI technology on the server side with FacePRO, the in-house facial recognition application, which uses AI deep learning capabilities. Moving ahead, they transitioned their knowledge of AI from the server side to the edge, introducing i-PRO security cameras with built-in AI capabilities last summer, alongside their own in-house analytics. Moreover, in line with the Panasonic approach to focus more on collaboration with specialist AI software developers, a partnership with Italian software company, A.I. Tech followed in September, with a range of intelligent applications, partially based on deep learning. Additional collaborations are already in place with more than 10 other developers, across the European Union, working on more future applications. i-PRO AI-capable security cameras Open systems are an important part of Panasonic’s current approach. The company’s i-PRO AI-capable cameras are an open platform and designed for third-party application development, therefore, applications can be built or tailored to the needs of an individual customer. Panasonic use to be a company that developed everything in-house, including all the analytics and applications. “However, now we have turned around our strategy by making our i-PRO security cameras open to integrate applications and analytics from third-party companies,” says Gerard Figols, Head of Security Solutions at Panasonic Business Europe. Flexible and adapting to specific customer needs This new approach allows the company to be more flexible and adaptable to customers’ needs. “At the same time, we can be quicker and much more tailored to the market trend,” said Gerard Figols. He adds, “For example, in the retail space, enabling retailers to enhance the customer experience, in smart cities for traffic monitoring and smart parking, and by event organisers and transport hubs to monitor and ensure safety.” Edge-based analytics offer multiple benefits over server-based systems Edge-based analytics Edge-based analytics offer multiple benefits over server-based systems. On one hand, there are monetary benefits - a cost reduction results from the decreased amount of more powerful hardware required on the server side to process the data, on top of reduction in the infrastructure costs, as not all the full video stream needs to be sent for analysis, we can work solely with the metadata. On the other hand, there are also advantages of flexibility, as well as reliability. Each camera can have its own individual analytic setup and in case of any issue on the communication or server side, the camera can keep running the analysis at the edge, thereby making sure the CCTV system is still fully operational. Most importantly, systems can keep the same high level of accuracy. Explosion of AI camera applications We can compare the explosion of AI camera applications to the way we experienced it for smartphone applications" “We can compare the explosion of AI camera applications to the way we experienced it for smartphone applications,” said Gerard Figols, adding “However, it doesn’t mean the hardware is not important anymore, as I believe it’s more important than ever. Working with poor picture quality or if the hardware is not reliable, and works 24/7, software cannot run or deliver the outcome it has been designed for.” As hardware specialists, Figols believes that Panasonic seeks to focus on what they do best - Building long-lasting, open network cameras, which are capable of capturing the highest quality images that are required for the latest AI applications, while software developers can concentrate on bringing specialist applications to the market. Same as for smartphones, AI applications will proliferate based on market demand and succeed or fail, based on the value that they deliver. Facial recognition, privacy protection and cross line technologies Panasonic has been in the forefront in developing essential AI applications for CCTV, such as facial recognition, privacy protection and cross line. However, with the market developing so rapidly and the potential applications of AI-driven camera systems being so varied and widespread, Panasonic quickly realised that the future of their network cameras was going to be in open systems, which allow specialist developers and their customers to use their sector expertise to develop their own applications for specific vertical market applications, while using i-PRO hardware. Metadata for detection and recognition Regarding privacy, consider that the use of AI in cameras is about generating metadata for the detection and recognition of patterns, rather than identifying individual identities. “However, there are legitimate privacy concerns, but I firmly believe that attitudes will change quickly when people see the incredible benefits that this technology can deliver,” said Gerard Figols, adding “I hope that we will be able to redefine our view of cameras and AI, not just as insurance, but as life advancing and enhancing.” i-PRO AI Privacy Guard One of the AI applications that Panasonic developed was i-PRO AI Privacy Guard Seeking to understand and appreciate privacy concerns, one of the AI applications that Panasonic developed was i-PRO AI Privacy Guard that generates data without capturing individual identities, following European privacy regulations that are among the strictest in the world. Gerard Fogils said, “The combination of artificial intelligence and the latest generation open camera technology will change the world’s perceptions from Big Brother to Big Benefits. New applications will emerge as the existing generation of cameras is updated to the new open and intelligent next generation devices, and the existing role of the security camera will also continue.” Future scope of AI and cameras He adds, “Not just relying on the security cameras for evidence when things have gone wrong, end users will increasingly be able to use AI and the cameras with much higher accuracy to prevent false alarms and in a proactive way to prevent incidents." Gerard Fogils concludes, “That could be monitoring and alerting when health and safety guidelines are being breached or spotting and flagging patterns of suspicious behaviour before incidents occur.”

What is the best lesson you ever learned from an end user?
What is the best lesson you ever learned from an end user?

Serving customer needs is the goal of most commerce in the physical security market. Understanding those needs requires communication and nuance, and there are sometimes surprises along the way. But in every surprising revelation – and in every customer interaction – there is opportunity to learn something valuable that can help to serve the next customer’s needs more effectively. We asked this week’s Expert Panel Roundtable: what was the best lesson you ever learned from a security end user customer?

What is the impact of remote working on security?
What is the impact of remote working on security?

During the coronavirus lockdown, employees worked from home in record numbers. But the growing trend came with a new set of security challenges. We asked this week’s Expert Panel Roundtable: What is the impact of the transition to remote working/home offices on the security market?