Steve Lasky, Editorial Director
SecurityInfoWatch.com
The paradigm shift in physical security from a reactionary and defensive proposition to a more proactive stance has characterized the migration of advanced analytics into almost every platform. Security end-user demanding systems that are faster and more intelligent, and at the same time cost-efficient and better suited for integrated solutions, are looking for more than technology that detects and deters. They now require systems that can digest vast amounts of data, then process autonomously monitored responses at lightning speeds. Upping the preemptive ante is a crucial step in the growth of intelligent physical security systems. And it is currently moving beyond the ubiquitous use of video surveillance analytics to other sensory devices at the edge and controlling access into and across the interior of a facility.
This improvement in security operations at the enterprise level is also addressing the convergence of physical and cybersecurity threats while easing the migration into a more defined digital world. As stated in a recent Security Industry Association (SIA) report: “Security will move beyond video surveillance and access control with features such as autonomous reporting, monitoring and response. Autonomous security systems will communicate with each other and with people and will act on their own to collect more information and trigger complex safety protocols. Security technology will operate with predictive intelligence and will be deeply integrated with building systems, including HVAC, lighting, elevators and fire alarm and suppression. Remote monitoring capabilities will be the norm and this interconnectivity will bring the Internet of Things (IoT), 5G edge sensors, mobile devices, body-worn cameras, robots, drones, contextual conversational AI and augmented reality together to provide frictionless access, risk analysis, and predictive behaviors for proactive responses with real-time machine intelligence.”
For example, says Sam Joseph, co-founder and chief executive officer of Hakimo, whose company develops software for the physical security industry powered by artificial intelligence (AI), “suppose you work at Google or any big enterprise and you have offices in San Francisco and in New York, and suppose you are in the San Francisco office, or somewhere on the west coast, logging into your email using single sign-on or any other standard techniques. If someone uses your badge or a cloned badge of yours in New York, these two pieces of information are stored in completely separate systems. No one will notice that there is no system connecting the two, and a security breach as obvious as this goes completely undetected today.”
Joseph, like many technologists who have made their way into the physical security industry because they see a sector that is moving forward despite itself, contends that physical security systems have lagged behind cybersecurity advancements for the previous two decades because many systems operators are overwhelmed with incoming data and constant alerts that distract more than inform and that is more than most humans can manage.
“This was a problem that cybersecurity faced in the 2000s. Fifteen, twenty years ago when cybersecurity systems started generating a lot of alerts, there was no way a human analyst or a human operator could monitor them all effectively,” Joseph continues, pointing out that the cybersecurity industry quickly developed tools like Security Information and Event Management (SIEM) and Orchestration, Automation and Response (SOAR) software to simplify the data tsunami. “Physical security has reached that point only now. And one reason convergence is getting delayed is that cybersecurity is way ahead in terms of tools and techniques. Physical security is still lagging behind. Our vision is to elevate physical security quickly to cybersecurity levels so that cases like the previous examples can be easily resolved.”
The Hakimo software streamlines the workflow of a global security operations center (GSOC) by freeing up time for operators and by surfacing security threats that would have gone unnoticed previously. The AI algorithms in the Hakimo software initially serviced video surveillance platforms, but working closely with security end-users, the need to rectify the GSOC logjams and improve security accountability of access control systems moved the solution in another direction.
“Security is not just about video. There is access control that can track patterns that every employee exhibits and so on. There are many applications beyond video for which we could use AI to detect anomalies, detect vulnerabilities and anomalous events. Even though we started out with video, there has been a natural progression to our product today based on customer feedback and based on our expertise in other industries like cybersecurity where AI has done important things,” says Joseph.
His team’s software application with its data analytics algorithms can also analyze alarms across time and diagnose faulty hardware, such as door sensors and sensors. Pointing out anomalies in cardholder behavior is a crucial tool for access control accountability. The software can point out impossible travel (the same card being used at multiple locations within a short duration which is physically impossible), unusual time or location of usage.
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