In a global security operations center (GSOC), decisions are being made at breakneck speed using information that comes in through video cameras, access control systems, fire alarms, intrusion detection platforms, intelligence feeds, phone calls, emails and many, many more. Add in new ways of monitoring trending information on social media or the dark web and there may be so much information incoming that it can be overwhelming for security leaders.
So what’s the answer to better decision-making within physical security? It starts with taking on the challenges traditional security leaders have faced and meeting them with completely new ideas. Here are a few:
The Challenge: Multiple disparate systems to manage.
In the past, an organization may have invested in a physical security information management (PSIM) to help integrate multiple unconnected security applications and devices. But the complexity – and the cost – of this kind of solution was cumbersome and often yielded minimal ROI.
The Solution: Data fusion.
Aiming to integrate data from siloed security systems – think video surveillance, access control points, fire and intrusion alarms, etc. – into a holistic view that enables users to quickly filter de-noised threat information relevant to the organization, is the way forward. Using a Security Fusion Platform™ instead of a PSIM broadens the capability of security leaders to pull in additional data points to better inform decisions, such as intel platforms and situational awareness data.
The Challenge: Expensive rip and replace to accommodate a PSIM.
In many cases, implementing a traditional PSIM involved months of designing, building and implementing a platform that is largely rooted in expensive, on-premise hardware.
The Solution: Scalable digital transformation.
We live in an instant gratification society and it’s unfair to think that the same doesn’t apply to a large corporation aiming to upgrade their physical security posture. Cloud-native platforms bring speed to the table, as well as the ability to properly scale as necessary and needed.
The Challenge: Too many false alarms.
Security operators are constantly addressing which alarms are “real” and which are false alarms. Many of these false alarms are considered “noise.” It becomes crucial then to differentiate between what is noise and what is intelligent information which can be researched and found viable.
The Solution: Addressing inefficiencies.
Bringing in data from multiple sensors and fusing them together creates more intelligence for security operators who are then better able to direct resources to a specific location. Using machine learning, a Security Fusion Platform pulls data from a company’s disparate monitoring systems and security sensors to provide operators the information to evaluate and respond to alerts without sifting through false alarms.
The Challenge: Sifting through incoming data.
Sometimes in a SOC, there are multiple workstations that contain solutions that must be accessed separately as an alarm comes in. That’s not only inefficient; it’s dangerous.
The Solution: Better, more streamlined decision-making.
Centralized monitoring and intelligence changes the way security leaders process information. By incorporating machine learning technology into a platform that fuses multiple data points together to garner better information, decisions are more streamlined and effective. This can also help organizations to move corporate safety operations from reactive-only responses to designing proactive programs that identify threats before they happen.
A lot of the challenges businesses face in their physical security programs stem from reactive programs and a lack of innovation. The solution to this is the adoption of a tech-forward approach that fuses data together to create a more seamless, proactive and effective response for physical security leaders.
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This article was originally published in the July edition of Security Journal Americas. To read your FREE digital edition, click here.
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