The digital footprint of Australian organisations is no longer confined to enterprise boundaries: public cloud adoption has risen steadily over the past few years; more than 80 percent of enterprises follow a hybrid work model; and the multi-access edge computing market is projected to grow from about US$ 100 million in 2024 to more than US$ 5 billion by 2033. With the attack surface expanding beyond the enterprise perimeter, securing remote infrastructure, operational technology networks and the digital edge, is becoming a top priority for Australian companies. Cybersecurity strategies are evolving to focus on borderless protection. The Australian Government’s 2023–2030 Cyber Security Strategy highlights the need for security-by-design and resilience across all digital layers; this includes endpoints and edge.
AI-first, platform-led approaches enabling real-time, local data processing and consolidated security management are playing a crucial role by mitigating security risks and supporting regulatory compliance across the distributed enterprise. This piece explores how Australian companies can use such approaches, particularly to secure their digital edge.
Real-time, integrated security at the edge
Organisations can look to leverage AI to perform real-time threat detection and other actions directly on their edge devices: think AI-powered cameras and sensors identifying security issues – potential data breach, non-compliance, etc. – in real-time, or devices processing sensitive data locally to reduce the risk of interception. Replacing fragmented, point solutions with a unified, scalable platform would create end-to-end visibility, enabling consolidation of security management across dispersed edge and IoT environments.
AI-enabled threat detection relies on machine learning and behavioural analytics to identify anomalous activity in real-time across distributed networks and edge devices. It counters cloud latency by processing data close to its source, thereby enabling threats to be detected and contained without delay. Gathering information from users, endpoints and networks, the models learn to distinguish between normal and abnormal behaviours; in case of a deviation in login, data access or other activity pattern, they automatically trigger remedial actions at the edge, preventing threats from moving further inside the enterprise environment. Besides instantaneity, benefits include detection of sophisticated – even unknown – threats, lower alert fatigue, and scalability.
In 2021, electricity provider CS Energy was hit by a ransomware attack that resulted in data loss, besides disruption of internal systems and customer services. As IT and OT (operational technology) systems become intricately connected, attackers breaching a single IT system can quickly penetrate critical OT infrastructure, for instance, turbines and distribution grids in electric utilities. Fortunately, organisations can now leverage AI to secure their OT networks, identifying anomalies in real-time to block cyberattacks before they shut down core systems.
Zero Trust, complete protection
The Zero Trust principle eliminates implicit trust in a distributed environment to ensure no user or device is trusted by default. Capabilities, such as continuous verification of identity, context and device health, and micro-segmentation of the network into tiny, isolated zones, make sure that only authorised users access resources even at the network’s edge. Besides preventing attackers from moving laterally through the network, Zero Trust shrinks the attack surface and extends consistent protection to users and resources, even those outside the enterprise perimeter.
Unified security everywhere
OT, cloud and endpoint environments managed in silos suffer from limited visibility (into threats, for example), operational inefficiencies, and delayed threat detection and response. A platform can unify security across all these environments to empower enterprises with centralised visibility and a coordinated threat response mechanism. Shared context and threat intelligence make it possible to secure the entire digital estate at once, ensuring that an attack in one environment does not progress into the others. Security policies can be managed centrally, minimising misconfiguration and enhancing compliance. A radiology provider with more than 15 locations and multiple endpoint devices and branches across Victoria and NSW implemented a Secure Access Services Edge (SASE) platform, unifying network infrastructure across clinics, offices and data centres to enhance cybersecurity across operations.
Other benefits of a unified platform include automated incident response – isolating the affected device or component, alerting the security team, and blocking traffic in the concerned cloud and OT networks – and simplified architecture, resulting in cost savings.
These reasons make an AI-first, platform-led approach the ideal solution for defending a growing digital estate against cyberattacks, and ensuring compliance with evolving regulations.
