India is home to some of the world's most bustling metropolises and vibrant cultural centres, with multi-faceted resources crammed into a relatively small patch of land. The country's diversity and high density provide a fertile ground for the type of innovation that powers tomorrow's industries but also createshides opportunities for those seeking to disrupt.
There are robust military facilities, bustling airports, highly productive plants, and cross-country infrastructure facilities requiring heightened vigilance, 24x7. And when it comes to the safety of these critical infrastructures, the way forward may be to adopt smarter strategies to help optimize manual effort. The focus should be onenabling a data-driven intrusion detection system (IDS).
In its recent report on the global market for IDS, Research firm Global Industry Analysts predicts that the market will reach $21.3 billion by 2026 at a CAGR of 11.9%. Going by the analytics capabilities that modern-day IDS could exhibit, there's no reason that shouldn’t happen.
The propositions favouring the tech-led growth of data-drivenIDS are pretty convincing: the ubiquity of wireless networks, the proliferation of smart devices, and an unrivalled digital trail will lead to an explosion of 'actionable' data. And it's a scenario that's ripe for the picking.
Customarily, intrusion detection has supplemented robust patrolling efforts with traditional point sensors, which passively monitor the environment for the presence of external threats. But as time has passed technology has evolved and the nature and scope of threats have evolved. The efficacy of many traditional methods has shrunk in terms of their coverage and the number of potential threats they detect. And missing out on any real-time alerts when they are most needed is a grave security error.
The answer to new-age problems lies in a new breed of sensing technology that contributes to continuous, 360-degree surveillance of the premises by factoring in every possible deviation and anomaly. An example of the same would be Distributed Acoustic Sensors that ATHENA employs. The solution aggregates real-time data about noise, pressure, and strain over large distances and applies modern data-analytics techniques to provide insights to enable more targeted responses.
Distributed Temperature Sensors, too, come in handy for keeping an eye out for unusual heat patterns and mapping them accordingly, thus defining the potential of a fire or a gas leak. It's the convergence of all these parameters that help to paint a clear picture of any security threat when it occurs.
Intrusion detection applications are not confined to regions with mild weather. Thanks to the use of Optical Fibre Cable (OFC), such sensors can operate in harsh environments. This is particularly beneficial for border security and monitoring utilities such as pipelines and other structural networks.
As a consequence of the increased mobility, wireless networks and IoT connectivity, varied sources of data are now at hand. And that’s great to serve the real-time demands of today’s nations and industrial establishments. The most effective way to leverage all this powerful data is by deploying advanced signal processing techniques in conjunction with AI/ML.
By layering AI/ML into the IDS, the system can be taught to read and identify patterns, thus making critical decisions to help optimize human intervention. It can be trained to detect various types of anomalies and act on them in real-time.
The result? Advanced signal processing and AI/ML work in tandem to filter, process, classify and discriminate between intrusion and false alarms. At times, nominal fence disturbances, for instance, could be mistaken for intrusions by an IDS, which is why the AI/ML can learn to distinguish between a real and a false alert. It's this data management and analytics capability that gives IDS the edge over traditional intrusion detection systems.
The LiDAR-based Intrusion Detection System exhibits another compelling case of synergistic data usage. By using the technology to capture real-time imagery and thus visualise the environment, aerial perspectives can be gathered as well. Visual analytics helps to detect intrusions from a unique viewpoint by factoring in the terrain and pinpointing the exact location of the intrusion. A series of LiDAR’s working in tandem could relay accurate data across devices to help detection and drive action.
Visualisation technologies are a must for any modern IDS. The framework is already present to exploit. Visual analytics data can be centralised, making it easier for stakeholders and decision-makers to access reports, spot trends and make critical decisions about future strategies.
Add video analytics into the mix, and you have an IDS system that goes beyond just 'inferring' and finding evidence that could prove conclusive. That makes it a genuinely formidable proposition for security personnel.
By now, you must have realised that an effective IDS deserves to be seen as an all-encompassing platform that draws in various sources to its fold. The addition of accessories, such as ONVIF compliant camera support, are integral parts of the package. And a range of enhancements is possible.
For example, IDS solutions constructed by ATHENA feature third-party VMS (video management system) integrations. This helps enhance the scope and coverage of recording, thus making it more comprehensive.
As the scope of application for IDS increases, so will the number of parameters and variables that might be encountered. The only way to keep pace with all these variegated demands is to employ technology that isn't stringent and can tap into all the available assets in use — the power of data, in particular.
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