In the world of cybersecurity, ethical hacking proactively identifies security vulnerabilities before malicious actors (i.e., unethical hackers) can exploit them. By simulating real-world attacks, organisations can strengthen defences, protect sensitive data, and maintain public trust. In the physical security world, ethical hacking can transform cybersecurity of security systems from a reactive struggle into a strategic safeguard. We asked our Expert Panel Roundtable: What is the role of ethical hacking as it relates to physical security?

Next-generation (Next-Gen) technologies are products, services, or infrastructures that represent a significant leap forward rather than a small, incremental update. In the physical security industry, NextGen products are those that enable disruptive change, breakthrough performance, and a fundamental change that renders previous products obsolete. We asked our Expert Panel Roundtable: What is the next generation of physical security solutions, and how will they change the industry?

Emphasising proactive rather than reactive security shifts the focus from dealing with crises and damage control to prevention. Advantages of a proactive approach include cost efficiency, better business continuity, and fewer crises that draw attention away from strategic improvements. Staying ahead of threats is a core mission of the security department, and technology has evolved to enable security professionals to deliver on that mission better than ever. We asked our Expert Panel Roundtable: How are security systems transitioning from reactive to proactive, and what is the benefit?

Multiple technology trends are transforming the physical access control market. There is a fundamental shift away from physical cards and keys toward digital identities — mobile credentials, digital wallets, biometrics, and cloud-native access platforms. These next generation access solutions are radically reshaping how buildings operate, protect staff, and perform functionally. At the same time, AI and analytics solutions are being layered onto these physical access control systems to support predictive threat detection and behavioural insights. Access data itself is becoming an asset for sustainability, space optimisation, and smart building initiatives. Risk, impact operations and experience The annual HID Global Security and Identity Trends Report highlights these and other issues The annual HID Global Security and Identity Trends Report highlights these and other issues. The survey cites improving user convenience as a priority for nearly half of organisations, while 41% are focused on simplifying administration, and 28% struggle with system integration. These are not theoretical challenges, they are day‑to‑day friction points that add cost, increase risk, impact operations and experience, and, of course, must be addressed. HID Global’s commercial focus HID Global’s commercial focus is to help organisations digitise their access control — with mobile identities, biometrics, and cloud platforms — and then to use the data to deliver more value. “We are turning access control from an operational cost into a software-driven asset that improves efficiency, supports Environmental, Social, and Governance (ESG) goals and even creates new revenue opportunities,” says Steven Commander, HID Global’s Head of Consultant Relations. The impact of digital transformation Digital transformation is the method of moving access control from hardware and physical credentials Digital transformation is in the process of moving access control from hardware and physical credentials to a software-driven, integrated experience. The transformation strengthens security while also improving user convenience — transforming the “pavement to the desk” journey. HID enables this shift through mobile credentials, biometrics, cloud-native platforms, and solutions that allow third-party applications to run on door hardware. “This helps customers turn access data into operational and commercial outcomes, while also improving the overall user experience,” says Commander.  Digital transformation in access control is not focused on chasing the latest trends. Rather, transformation is about turning software, data and integration into outcomes that matter to customers, says HID. “Security becomes stronger and more adaptive,” says Commander. “Operations become simpler and more cost‑effective. Experiences become seamless and consistent. Sustainability moves from ambition to action. And the financial case becomes clearer as efficiencies are banked and new value streams emerge.” The challenge of futureproofing with long lifecycles Given that physical security technologies will be in place for 15 to 20 years, it is important to plan for how systems can evolve over time. Considering how rapidly security threats, compliance standards, and user expectations change, 15 to 20 years is a long time. The decisions made at the beginning of a system’s lifecycle can either limit flexibility later (which will be costly) or enable long-term adaptability. Support for open standards such as Open Supervised Device Protocol (OSDP) is therefore important Choosing products and platforms that are open, interoperable, and designed for updates can enable future-proof projects. Support for open standards such as Open Supervised Device Protocol (OSDP) is therefore important.  In addition, systems built on open controller platforms — such as Mercury — enable organisations to switch software providers or expand functionality without replacing core door hardware. Architectural openness is key to system lifecycles and maximising the return on investment (ROI) from a chosen solution. Digital credentials and mobile access Flexibility and upgradeability should also be top of mind when it comes to endpoints like access control readers. While RFID cards are still commonplace, there is a clear trend toward digital credentials and mobile access. Readers that support both allow organisations to transition at their own pace, without committing to a full system overhaul. A long system lifecycle does not mean technology should remain static. Security, particularly cybersecurity, demands more frequent updates. Technologies that support firmware upgrades in the field extend the value of a deployment while helping organisations keep pace with emerging threats. In that sense, lifecycle thinking is not just about longevity — it’s about maintaining resilience and readiness over time. Applying biometrics and mobile identities Biometrics is becoming mainstream as a credential alternative, strengthening security without adding friction Biometrics is becoming mainstream as a credential alternative, strengthening security without adding friction. Many organisations are now deploying biometrics to support fast, seamless access journeys, with adoption already around 39% in access control according to HID’s recent research.  In addition, 80% of organisations surveyed expect to deploy mobile identities within the next five years. Full technology integration enables tap‑to‑access without opening an app; the user journey becomes faster, safer, and more convenient. “It is where the industry is headed and we are at the vanguard of this,” says Commander.    Ongoing challenge of cybersecurity At HID Global, cybersecurity is embedded into everything, from corporate processes and development practices to the solutions they bring to market. “Our approach ensures that customers can strengthen their overall security posture, not only by deploying secure products but by benefitting from HID’s commitment to the highest industry standards,” says Commander. HID holds multiple globally recognised certifications, including ISO 27001, ISO 14298, SOC Type 2 and CSA STAR, which demonstrate their robust information security and cloud security practices. In addition, HID’s SEOS® secure chipset is independently SEAL-certified, providing one of the most advanced levels of protection available on the market today. “Ultimately, this means organisations are not just purchasing isolated secure products; they are implementing solutions developed and delivered within a comprehensive, cybersecure framework,” says Commander. “When deployed according to best practices, HID solutions enable customers to achieve the highest levels of resilience against evolving physical and cyber threats.” Developing green and sustainable solutions A huge amount of waste is generated from the manufacture of plastic RFID access cards Digital credentials align with the sustainable solutions that everyone wants. A huge amount of waste is generated from the manufacture of plastic RFID access cards. Over 550 million access cards are sold annually. This creates 2,700 tons of plastic waste and 11,400 tons of carbon, based on a PVC card weighing 5 grams.  Therefore, digital credentials self-evidently reduce the reliance on plastic cards (helping reduce carbon emissions by up to 75% according to HID’s research), while leveraging access control system data supports energy optimisation by shutting down or reducing systems in unused spaces. Energy use and CO₂ emissions can be cut dramatically, showing how access systems can contribute to sustainability goals and green building certification. What is the latest in smart buildings? Smart buildings increasingly rely on mobile access control as the backbone for digital services. Real-time access data enables new services such as automated room bookings, HVAC control, lift/elevator calling, e-bike hiring, and so on. Smart buildings increasingly rely on mobile access control as the backbone for digital services The financial upside is clear; smart, digitally transformed buildings can deliver around 8% higher yields per square foot versus traditional office space. Operational savings accrue from reduced administration, the removal of card production and shipping, and lighter IT support. This creates a value cycle — better experiences drive adoption, adoption fuels monetisation, and monetisation funds further improvements. Achieving technology impact in the real world One standout project is One Bangkok – a $3.9 billion mixed used development in Thailand – which demonstrates the scale of what can be achieved when access control data is used for optimisation, particularly when it comes to monitoring facilities usage and occupier behaviours. By switching lights off or lowering the temperature in unused rooms, for example, the One Bangkok building demonstrates this potential with a 22% reduction in energy consumption, saving 17,000 MWh and 9,000 tons of CO₂ annually.  Sustainability is a key factor in contributing to how properties are valued. And sustainability extends far beyond digital credentials having a lower environmental impact than plastic cards.  Buildings with recognised sustainability certifications often command rental premiums of around 6%, and three‑quarters of security decision‑makers now consider environmental impact in their procurement assessments.

Matrix Comsec, a technology company delivering enterprise-grade solutions in security and telecommunications, has been recognised among Gujarat's Top 50 SMEs and named a winner in the Best Manufacturing SMEs category at the inaugural Top 50 SME Awards - Gujarat, an initiative of Axis Bank and India SME Forum. For Matrix, the recognition is not the culmination of a single initiative. It acknowledges an operating philosophy built over time: create original technology, retain ownership across the product journey and turn engineering intent into dependable products through disciplined manufacturing. Purpose-built solutions At the centre of this approach is an integrated product-development ecosystem. Hardware, software, firmware, mechanical engineering, certification and manufacturing operate as connected capabilities. This alignment gives Matrix control over how an idea is designed, validated, produced and supported, while helping it address real customer requirements with purpose-built solutions. Matrix builds quality into every stage—from selecting materials and manufacturing products to testing, delivery and product performance. Clear processes, regular reviews and smart automation help teams identify issues early, maintain consistency and work more efficiently. This enables Matrix to grow without compromising speed, reliability or quality. The same approach continues beyond the factory. Matrix brings together its research, manufacturing, sales and business partners to understand customer needs, deliver projects smoothly and support long-term success. This connected way of working creates lasting value for customers, partners and the industry as a whole. Multi-stage evaluation “At Matrix, world-class products are built through original engineering, disciplined manufacturing, measurable quality and shared accountability. Our strength comes from the systems we have established, the principles we consistently follow and the people who bring them to life every day. Being recognised among Gujarat’s Top 50 SMEs is a valued acknowledgement of this collective effort and an important milestone in our continuing journey to innovate, improve and set higher standards,” said Ganesh Jivani, CEO & MD, Matrix Comsec. Matrix earned its place among Gujarat’s Top 50 SMEs through a rigorous, multi-stage evaluation conducted by an independent jury of distinguished business leaders and industry experts. This recognition marks another significant milestone in Matrix’s journey of creating globally relevant technology from India—driven by original thinking, consistent execution and an enduring commitment to Expect More.

Cyber threats are becoming faster, more sophisticated, and increasingly difficult to detect using traditional security operations alone. As organisations adopt AI-powered Security Operations Centre (AI SOC), measuring success requires more than simply counting alerts or incidents. The real value of an AI SOC lies in how effectively it improves detection, accelerates response, enhances analyst productivity, and strengthens business resilience. In this article, you will learn which AI SOC metrics matter most, why they are important to both security teams and business leaders, and how artificial intelligence helps improve performance across every stage of the security operations lifecycle. You will also discover how organisations can use these metrics to continuously optimise their security posture while demonstrating measurable business value. Traditional security operations Security teams generate enormous amounts of operational data every day. Without meaningful performance measurements, it becomes difficult to determine whether security investments are delivering real improvements or simply producing more alerts. Effective AI SOC metrics provide visibility into the speed, quality, and efficiency of security operations. They allow organisations to identify operational bottlenecks, justify technology investments, improve workflows, and reduce overall cyber risk. Unlike traditional SOC, AI-powered SOC continuously learn from historical incidents, enrich alerts with contextual intelligence, automate repetitive tasks, and help analysts focus on genuine threats. Measuring these improvements requires looking beyond simple incident counts and focusing on operational outcomes. Hidden attack patterns One of the most important cybersecurity metrics is Mean Time to Detect (MTTD). This measures the average amount of time required to identify a security incident after it begins. The shorter the MTTD, the less opportunity attackers have to move laterally through networks, escalate privileges, or access sensitive information. Every minute saved during detection can significantly reduce the overall impact of a cyber attack. AI dramatically improves MTTD by analysing millions of events in real time. Machine learning models recognise subtle behavioural anomalies that would likely be missed by manual monitoring or rule-based detection systems. AI also correlates seemingly unrelated events across endpoints, cloud environments, user identities, and network traffic to reveal hidden attack patterns much earlier. Instead of analysts manually reviewing thousands of alerts, AI prioritises suspicious activity almost instantly, allowing investigations to begin sooner. Reducing reputational damage Detection alone is not enough. Once a threat has been identified, security teams must respond quickly to contain and remediate the incident. This is measured through Mean Time to Respond (MTTR). MTTR reflects the average time required to investigate, contain, eliminate, and recover from a security incident. Faster response limits operational disruption, minimises financial losses, and reduces reputational damage. AI-powered SOC significantly reduce MTTR by automating many response activities. Security orchestration workflows can isolate compromised devices, disable suspicious user accounts, block malicious IP addresses, gather forensic evidence, and notify appropriate teams without waiting for manual intervention. AI also assists analysts by automatically summarising incidents, recommending next steps, identifying affected assets, and highlighting similar historical attacks. Rather than spending valuable time collecting information, analysts can focus on making informed decisions. Performing routine investigations Security talent remains one of the industry's most valuable and limited resources. Measuring analyst productivity helps organisations understand whether their security teams are spending time on high-value investigative work or becoming overwhelmed by repetitive tasks. Traditional SOC analysts often spend large portions of their day reviewing false positives, manually correlating alerts, searching multiple data sources, and performing routine investigations. AI changes this workflow considerably. Automated alert enrichment provides analysts with relevant threat intelligence, asset context, user information, vulnerability data, and attack history before an investigation even begins. Intelligent prioritisation ensures analysts work on incidents that represent the greatest organisational risk. Reducing operational costs As a result, analysts can investigate more incidents, resolve them faster, and spend more time on proactive activities such as threat hunting, security improvement, and strategic planning. Higher analyst productivity also contributes to reduced burnout, improved job satisfaction, and better staff retention, all of which are critical challenges facing modern SOCs. Another valuable operational metric is alert quality. Large numbers of false positives create alert fatigue, causing analysts to waste time investigating benign activity while genuine threats compete for attention. AI improves alert quality by combining behavioural analytics, threat intelligence, contextual enrichment, and historical patterns to determine the likelihood that an alert represents a real attack. Rather than simply increasing the number of detected events, AI helps ensure that security teams receive fewer but more meaningful alerts. This improves investigation efficiency while reducing operational costs. Predefined response actions An increasingly important AI SOC metric is automation rate. This measures the percentage of security tasks completed automatically without requiring analyst intervention. Examples include automated alert enrichment, phishing analysis, malware classification, log correlation, incident ticket creation, evidence collection, and predefined response actions. Higher automation rates allow security teams to manage larger environments without proportionally increasing staffing levels. Analysts remain responsible for strategic judgement and complex investigations while AI handles repetitive operational tasks. Technical metrics alone do not fully demonstrate the value of an AI SOC. Senior executives increasingly want to understand how cybersecurity investments contribute to broader business objectives. Managing cyber risk Business-focused metrics may include reduced operational downtime, lower incident recovery costs, improved regulatory compliance, faster audit preparation, increased customer trust, and reduced financial risk. An effective AI SOC should align security performance with organisational goals. Demonstrating improvements in operational resilience and business continuity often provides stronger justification for continued cybersecurity investment than technical statistics alone. Imagine if the organisation reduced its average detection time from six hours to six minutes. How would that change the financial impact of a ransomware attack, customer confidence, and the executive team's ability to manage cyber risk? Questions like these help organisations view cybersecurity as a business enabler rather than simply a technical necessity. Continuous operational improvement Metrics should never be viewed as static reports produced once each month. Instead, they should support continuous operational improvement. AI SOC platforms provide real time dashboards that monitor performance trends, identify recurring bottlenecks, and highlight opportunities for optimisation. Security leaders can compare historical performance, evaluate new technologies, measure process improvements, and refine response playbooks using objective data. As AI models continue learning from new incidents, security operations become progressively faster, more accurate, and increasingly efficient. Broader business outcomes Organisations that regularly review and act upon these metrics are better positioned to adapt to evolving cyber threats while maintaining operational excellence. AI-powered Security Operations Centres are transforming how organisations detect, investigate, and respond to cyber threats. Measuring success requires focusing on meaningful operational metrics such as Mean Time to Detect, Mean Time to Respond, analyst productivity, automation rates, alert quality, and broader business outcomes. Together, these metrics provide a comprehensive picture of security performance while helping organisations continuously strengthen their cyber resilience. Rather than replacing security professionals, AI empowers them with faster insights, richer context, and intelligent automation that enables more effective decision making.

Traditional security tools generate enormous volumes of alerts, making it increasingly difficult for Security Operations Centre (SOC) teams to distinguish genuine threats from harmless activity. As organisations face growing attack surfaces and increasingly complex IT environments, effective threat detection has become one of the most important capabilities in modern cyber security. Detection engineering has emerged as a critical discipline that enables organisations to identify malicious activity accurately and efficiently. Combined with artificial intelligence (AI), detection engineering is helping SOCs reduce false positives, uncover advanced threats, and respond to incidents with greater speed and confidence. Complex IT environments In this article, users will learn what detection engineering is, why it has become an essential component of modern security operations, how AI is transforming the way detections are created and maintained, and why organisations are increasingly investing in AI-powered detection engineering to strengthen their cyber resilience. Detection engineering is the process of designing, developing, testing, and continuously improving security detection rules that identify malicious or suspicious behaviour within an organisation's environment. Rather than relying solely on default alerts supplied by security vendors, detection engineers create customised detection logic tailored to an organisation's specific risks, infrastructure, and threat landscape. Security detection rules The primary objective is simple. Detect attacks as early as possible while minimising unnecessary alerts that waste valuable analyst time. Detection engineering combines several disciplines, including threat intelligence, attack simulation, log analysis, behavioural analytics, adversary emulation, and continuous testing. Detection engineers analyse how attackers operate, identify observable behaviours, and convert those observations into detection rules that security platforms can monitor automatically. Instead of asking whether malware exists on a device, detection engineering asks broader questions such as whether an employee account is behaving unusually, whether privileged access is being abused, or whether multiple seemingly harmless activities together indicate an active attack. Identity monitoring solutions Many organisations deploy powerful security technologies such as Security Information and Event Management (SIEM), Endpoint Detection and Response (EDR), Network Detection and Response (NDR), cloud security platforms, and identity monitoring solutions. However, these technologies are only as effective as the detection logic behind them. Out-of-the-box detection rules are designed to work across thousands of organisations, meaning they often lack the context needed for a specific business environment. This can result in excessive false positives, missed attacks, or alerts that provide little actionable information. Evolving detection programme Detection engineering addresses these shortcomings by ensuring detections are continuously refined as new threats emerge. Instead of treating security as a static configuration, organisations create an evolving detection programme that adapts alongside attackers. Effective detection engineering is an ongoing process rather than a one-time activity. It typically begins with understanding current threat intelligence. Detection engineers study adversary tactics, techniques, and procedures, often using frameworks such as MITRE ATT&CK to understand how attackers operate throughout the attack lifecycle. Identify suspicious behaviours Next, engineers determine what telemetry is available from endpoints, networks, cloud environments, applications, identity systems, and security tools. Without high-quality data, even the best detection logic cannot perform effectively. Detection rules are then developed to identify suspicious behaviours rather than relying solely on indicators of compromise. These rules are thoroughly tested using attack simulations and red team exercises before being deployed into production. Once deployed, detections are continuously monitored. False positives are reduced, detection gaps are identified, and new intelligence is incorporated to ensure rules remain effective against evolving threats. Signature-based detections Artificial intelligence is fundamentally changing how detection engineering is performed. Rather than replacing human expertise, AI significantly enhances the speed, scale, and accuracy of detection development. AI can analyse vast quantities of security telemetry that would be impossible for humans to review manually. It identifies hidden relationships between events, discovers behavioural anomalies, and recommends new detection opportunities based on emerging attack patterns. Machine learning models continuously learn from historical incidents, allowing them to identify deviations from normal behaviour that traditional signature-based detections may overlook. Experienced security engineers For example, instead of simply detecting repeated failed login attempts, AI may identify a subtle combination of unusual login times, unfamiliar devices, abnormal data access patterns, and unexpected privilege escalation. Individually these events may appear harmless, but together they could indicate a compromised account. This behavioural approach enables organisations to detect sophisticated attacks much earlier in the attack lifecycle. Developing high-quality detection rules has traditionally required experienced security engineers who spend considerable time analysing logs and researching attacker behaviour. AI accelerates this process by suggesting detection logic based on threat intelligence, previous incidents, and behavioural analysis. Engineers can review and refine these recommendations rather than creating every detection manually. Relevant detection logic This allows security teams to respond much faster when new attack techniques emerge. Imagine discovering a new ransomware campaign targeting the industry. Instead of spending days researching indicators and building detection rules manually, AI can recommend relevant detection logic within minutes, allowing analysts to validate and deploy protections rapidly. Security analysts often spend much of their day investigating alerts that ultimately prove harmless. This reduces productivity and increases the likelihood that genuine threats will be overlooked. AI improves detection accuracy by enriching alerts with additional context before they reach analysts. It correlates information from multiple security platforms, asset inventories, user identities, threat intelligence feeds, and historical behaviour. Monitoring detection performance Rather than presenting an isolated alert, AI provides a richer picture of what is happening across the environment. As a result, analysts spend less time gathering information and more time investigating incidents that genuinely require attention. Attack techniques evolve constantly. Detection rules that worked effectively six months ago may no longer identify today's threats. AI enables continuous optimisation by monitoring detection performance over time. It identifies rules generating excessive false positives, highlights gaps where attacks were missed, and recommends adjustments based on new intelligence. Emerging attacker techniques This creates a living detection programme that evolves alongside both the organisation and the threat landscape. Threat intelligence identifies emerging attacker techniques, while detection engineering converts that intelligence into actionable detection rules. AI strengthens this relationship by automatically analysing global threat intelligence, identifying tactics relevant to the organisation, and suggesting detection improvements accordingly. This dramatically reduces the time between learning about a new threat and deploying effective monitoring capabilities. As organisations continue adopting cloud services, hybrid infrastructure, Internet of Things devices, and AI-enabled applications, the volume of security data will continue to grow. Future detection engineering will become increasingly automated, predictive, and intelligence-driven. AI will not only identify threats faster but will also recommend new detections, validate existing rules, simulate attacker behaviour, and help security teams continuously improve their defensive posture. Organisations that combine skilled detection engineers with AI-powered security operations will be far better positioned to identify sophisticated threats before they develop into major incidents.

Every day, organisations receive thousands of alerts from multiple security tools, alongside a large volume of threat intelligence from commercial feeds, open-source platforms, industry reports, and internal monitoring systems. Turning this information into meaningful security decisions is one of the biggest challenges today's Security Operations Centres (SOCs) face. Artificial intelligence (AI) is changing the way organisations analyse threat intelligence. Rather than simply collecting more data, AI enables security teams to understand which threats matter most, why they matter, and how they should respond. By enriching security data with context, correlating events across multiple sources, and prioritising incidents automatically, AI helps security teams make faster and more informed decisions. Emerging attack trends In this article, users will learn what threat intelligence analysis involves, why traditional approaches struggle to keep pace with modern attacks, and how AI enhances context enrichment, automated prioritisation, and decision-making within today's SOC. Threat intelligence is the process of gathering, analysing, and interpreting information about cyber threats that may target an organisation. This information can include indicators of compromise (IOCs), attacker tactics and techniques, malware behaviour, phishing campaigns, exploited vulnerabilities, threat actor profiles, and emerging attack trends. Detecting suspicious activity High-quality threat intelligence helps organisations answer important questions. These can include: who is attacking organisations similar to ours? Which vulnerabilities are currently being exploited? What techniques are attackers using? Which assets face the greatest risk? When analysed effectively, threat intelligence allows organisations to move from reactive defence to proactive security. Rather than waiting for attacks to occur, security teams can anticipate threats, strengthen vulnerable systems, and detect suspicious activity much earlier in the attack lifecycle. Modern organisations consume threat intelligence from dozens of different sources. Internal logs, endpoint detection platforms, SIEM solutions, vulnerability scanners, cloud security tools, government advisories, and commercial intelligence feeds all produce valuable information. Endpoint detection platforms Unfortunately, the sheer volume of data often becomes a problem. SOC analysts must determine whether an alert represents a genuine attack, whether it matches known threat actor behaviour, whether similar activity has already been observed, and whether the organisation's critical assets are at risk. Performing these investigations manually takes considerable time and experience. At the same time, attackers continually evolve their techniques. New malware variants appear daily, vulnerabilities are exploited within hours of disclosure, and sophisticated adversaries frequently modify their tactics to evade traditional detection methods. Without intelligent automation, security teams can struggle to separate genuine threats from background noise. Relevant intelligence automatically AI significantly improves threat intelligence analysis by processing enormous volumes of structured and unstructured data far faster than human analysts. Machine learning models identify relationships between seemingly unrelated events. Natural language processing can analyse threat reports, security blogs, vulnerability disclosures, and research publications to extract relevant intelligence automatically. Pattern recognition algorithms identify behaviours that match known attack techniques, even when attackers make slight modifications. For example, AI can correlate an unusual login, suspicious network traffic, abnormal endpoint behaviour, and recently published threat intelligence into a single investigation. Rather than analysing each alert individually, analysts receive a complete picture of the potential attack. This dramatically reduces investigation time while improving detection accuracy. Sensitive financial systems An isolated IP address or malicious file hash provides limited value on its own. Once enriched with additional context, however, it becomes far more meaningful. AI automatically enriches security events using information such as known threat actor activity, malware families, vulnerability databases, geolocation data, historical attack patterns, asset criticality, business ownership, user behaviour, and previous incidents. Imagine an organisation receives an alert involving an employee login from an unfamiliar country. Without context, analysts may simply investigate the login. With AI-driven enrichment, the system may identify that the IP address has recently been associated with ransomware operations, the employee account has privileged access to sensitive financial systems, the login occurred outside normal working hours, and similar activity preceded attacks against organisations in the same industry. High-priority incident Suddenly, what appeared to be an isolated login becomes a high-priority incident requiring immediate action. Context transforms information into actionable intelligence. One of the greatest challenges facing SOC analysts is alert fatigue. Thousands of daily alerts make it impossible to investigate everything equally. Many alerts represent false positives, duplicate events, or low-risk activity that consumes valuable analyst time. AI addresses this problem through intelligent prioritisation. Rather than assigning identical importance to every alert, AI evaluates multiple factors simultaneously. These include the confidence of threat intelligence sources, attack techniques being used, affected assets, exploit availability, vulnerability severity, business impact, user behaviour, and previous incident history. Single investigative view Analysts can immediately focus on incidents that pose the greatest organisational risk while lower-priority events are investigated automatically or queued for later review. This approach reduces analyst workload while improving overall security outcomes. Effective security depends on making accurate decisions quickly. AI continuously correlates information across security technologies that traditionally operate independently. Endpoint alerts, firewall logs, identity systems, cloud activity, email security events, vulnerability management platforms, and external intelligence feeds all contribute to a single investigative view. This unified perspective allows analysts to understand not only what is happening, but also why it matters. Overwhelming volumes of alerts Instead of switching between multiple dashboards and manually comparing data, analysts receive an investigation that already contains the relevant evidence, supporting intelligence, recommended actions, and confidence scores. With this feature, decision-making becomes faster, more consistent, and more accurate. Consider this question: If your SOC could instantly understand the context behind every alert, how much sooner could your organisation detect and stop its next major cyber attack? This shift allows security teams to become more proactive rather than constantly reacting to overwhelming volumes of alerts. Making informed decisions Threat intelligence is no longer simply about collecting indicators or subscribing to additional intelligence feeds. Success depends on understanding relationships, identifying context, prioritising risk, and making informed decisions at speed. AI enables organisations to achieve these goals by enriching data automatically, correlating events across diverse security platforms, prioritising incidents according to real business risk, and accelerating investigations without sacrificing accuracy. As cyber threats continue to evolve, organisations that combine AI-powered intelligence with skilled security professionals will be far better positioned to detect attacks early, respond effectively, and strengthen their overall cyber resilience.

Milestone Systems, a provider of open platform video management software (VMS), is helping Resorts World Las Vegas (RWLV) bring together security operations, investigations, gaming compliance, and operational intelligence through an open platform video ecosystem built on Milestone XProtect VMS. Located on the iconic Las Vegas Strip, Resorts World Las Vegas is one of the newest and most technologically advanced resorts in the United States. Opened in 2021, the $4.3 billion property spans 88 acres and includes multiple hotel brands, a large casino floor, entertainment venues, retail spaces, and dining experiences that collectively attract thousands of guests each day. Diverse set of technologies Managing safety, compliance, and operational efficiency at this scale requires highly reliable and flexible video technology capable of supporting thousands of cameras and multiple specialised applications. Milestone XProtect VMS serves as the backbone that connects approximately 5,800 cameras and multiple best-of-breed technologies. The open architecture enables Resorts World to integrate a diverse set of technologies that support gaming surveillance, fraud detection, forensic investigations, business intelligence, and operational analytics while allowing operators to work from a consistent interface. "We rely on the system every day to investigate fraud, theft, and any activity that could result in a loss. It gives us the visibility we need to quickly understand what happened and take action," said Lindsay Dever, CFE, Assistant Director of Fraud & Nightclub Surveillance, Resorts World Las Vegas. Supporting regulatory requirements The full security system integrates camera technologies from Axis Communications, Bosch, and Hanwha Vision, while BriefCam supports forensic video review, people counting, and heat mapping. Oosto provides facial recognition capabilities, Aeyesky supports card-counting and cheating detection, and AXIS Case Insight helps analyse foot traffic and customer behavior. “Large, dynamic environments like Resorts World Las Vegas require technology that can adapt to multiple operational needs without adding complexity,” said Tim Palmquist, VP Americas, Milestone Systems. “An open platform approach allows this Las Vegas casino resort to bring together best-of-breed technologies into a single ecosystem, enabling teams to improve investigations, support regulatory requirements, and generate operational insights that extend well beyond traditional security.” Time-sensitive investigations Resorts World Las Vegas is able to respond to incidents more quickly, conduct investigations more efficiently, and support law enforcement with speed and confidence. The impact is particularly evident during time-sensitive investigations. Looking ahead, the resort plans to expand its use of AI-driven capabilities, including enhanced people counting, behavioural analytics, and tools that can better track guest movement across the property. Future enhancements will also focus on streamlining operator workflows and creating a more proactive approach to investigations.

PPLD serves El Paso County across multiple branches — from busy urban libraries to new rural buildings. Its security program, built on systems dating back to the late 1980s, had to keep pace with a fast-growing footprint. “I don’t know that we would have been able to get to the point where we had everything we wanted deployed if we didn’t have tech like this,” said Michael Brantner, Chief Facilities & Security Officer, Pikes Peak Library District. Pikes Peak Library District (PPLD) is one of Colorado Springs’ most-used public institutions, serving the El Paso County community across multiple branches with 780 cameras and more than 150 doors under active monitoring. Their physical security program had been trying to keep pace. Legacy systems dating back to the late 1980s. Cameras and access control systems that didn’t talk to each other. A small team buried under too many alarms. The model was reactive, and it was overdue for a rethink. Legacy security technology The challenge - PPLD’s footprint was growing in a few ways, through new construction and the addition of more rural buildings under its umbrella – and Chief Facilities & Security Officer Michael Brantner needed more visibility across all of the buildings. Combining the systems in place to protect these locations, plus the new ones, required a new approach: bring decades of legacy security technology into a unified, modern operation that could scale alongside the district’s growth. PPLD wanted to centralise the management of the district’s security function, which led Michael to explore the creation of a new security operations center (SOC). “We had a lot of technology that didn’t talk to each other,” Michael said. “We wanted to be able to consolidate it into one place where we can manage what’s happening across our sites.” Consolidate disconnected systems When he started building PPLD’s SOC, the mandate was clear: bring decades of legacy security technology into a unified, modern operation that could scale alongside the district’s growth. But he also needed to consolidate disconnected systems, prove ROI to the C-suite, and staff and train a team that could actually move the program forward. At the time, PPLD’s setup was a patchwork: Cloud-based cameras and access control sitting next to legacy equipment, with no shared view across them Operators who were refreshing screens to see new alarms Panic alerts, door alarms, and intercom calls each requiring a different screen, a different workflow, and a different response Notifications were inconsistent Response times couldn’t be measured No centralised SOC to manage alarms cohesively Residents experiencing homelessness Most incoming alarms generated by PPLD’s ACS were false: held-open doors, cleaning crews, and after-hours trip alarms. But every single alarm still demanded a response from someone on the team, even if there was no safety issue. The complexity was real. PPLD’s branches serve a diverse community that includes families, students, and residents experiencing homelessness across locations with very different security profiles. Some deal with routine access events. Others face behavioural incidents, policy enforcement issues, and higher alarm volumes. Across all of them, public spaces had to stay public, and private staff areas had to stay private. Those boundaries need to be enforced, all day, every day. Access control systems The solution - As Michael stood up PPLD’s new SOC, HiveWatch stood out as a way to centralise the security program and allowed the growing team a single, active view of every incident across every system. The platform connected directly to PPLD’s existing cameras and access control systems. This meant operators were able to view door alarms, access events, video clips, panic alerts, and environmental sensors (including vape and smoke detection) in one single incident list in a web-based browser. Instead of refreshing screens and guessing at what they might have missed, operators could see every active incident and incoming alarm the moment it surfaced and respond from the same place. Killing redundant alerts Alarm deduplication cut volume on day one, killing redundant alerts before they hit an operator. Noisy doors became easy to spot and fix. When specific issues surfaced, like a flood of DHO alarms, for instance, the system helped the SOC adjust alarm timing. That adaptability, tuned to actual door and user behaviour without loosening security, kept the program compliant and cut the alarm load the SOC had to manage. Operators, along with field officers, made use of the mobile app, too. The team’s ability to acknowledge, investigate, and resolve incidents from anywhere in the building was a huge benefit. Security triage stopped being tied to a desk. Response became coordinated, in real time, across every location. Standard operating procedure But the shift went beyond operations. For the first time, PPLD’s leadership had detailed data on its security program: response times, alarm volumes, and incident trends. Michael could walk into a leadership meeting with numbers that proved the program’s value. He could spot which operators were hitting targets, which branches were generating outliers, and where more operator or officer training was needed. “We aren’t just operators staring at cameras anymore. HiveWatch lets us cut through the noise, focus on what matters, and actually expand what our team can do,” said Joe Vickous, SOC Supervisor, Pikes Peak Library District. Single active queue Every shift, PPLD’s operators manage a single active queue. Door forced at a branch. Vape detection in a restroom. Held-open back door after a cleaning crew shift change. An intercom call from a side entrance. All surfaced in one view without screen-refreshing or system-hopping. When an access control alert comes in, the response is immediate. The operator sees the alert with the connected camera feed in the same view, follows the built-in standard operating procedure (SOP), and, if warranted, dispatches the field officer with full context from within the platform. Audible alerts mean the SOC can run HiveWatch in a single tab without sacrificing a full monitor, freeing operators to handle more important work like footage pulls, door testing, and badge creation between incidents. Badge creation between incidents “HiveWatch makes the operators more flexible and makes them more versatile, as well,” Michael said. “They’re able to focus on something else and it will prompt them and say, hey, pay attention. We have to interact. They can check it out, dispatch somebody, and then go back to what they’re doing.” And when something crosses the public-private line, such as a patron drifting into a staff-only corridor, the platform surfaces it in real time. The operator sees it, the field officer responds, and the boundary holds. Public stays public. Private stays private. No guessing. No discovery after the fact. Incidents are caught early, handled according to protocol, and documented with a full record attached. “The biggest benefit for us is having the tool that sorts through the noise and focuses the operators on the notifications that are actually coming in that need attention,” Branter said. Standard operating procedure The results: Median time to acknowledge incidents of 21 seconds and median time to resolve of 28 seconds using HiveWatch. Scaled the SOC from 2 operators to 6 plus a manager, with the platform absorbing the workload increase. Extended the SOC beyond the control room with mobile triage and response for field officers and operators. Equipped leadership with real-time data on acknowledgement and response times, and alarm trends, turning a reactive program into a proactive, measurable one. Positioned the program to absorb 800 additional cameras and access points without proportional headcount growth.

Paxton’s new Solo system is giving student housing providers a simpler way to manage access at scale. This case study looks at how JPR Fire, Security and Data used the phone-based, cloud-hosted security system to modernise access for around 500 students without the need for network infrastructure. Homes for Students provide 235 student housing properties across the UK and Ireland. JPR Fire, Security and Data provide the security system for the One London Road site in Newcastle-under-Lyme. Access control solution Until recently, the housing was secured using a classic standalone access control solution requiring no network infrastructure. The existing system was becoming difficult to manage, with approximately 500 residents across 5 blocks, including the onsite gym. Registered students gain access by entering a valid access code or presenting their fob. The site managers were continuously replacing lost fobs, creating additional running costs for the system. Mike Gater, Department Manager at JPR Fire, Security and Data, approached the site after attending Paxton’s launch event for Solo; a phone-based, cloud-hosted access control system. Mike saw the opportunity to upgrade the site to a more modern solution. Cost-effective option Solo is a smart, convenient, connected access control system. With the simplicity of standalone and the power of a networked solution; Solo is designed to make access control a simple, cost-effective option where a smartphone is used to administer the system and gain access through the door. With the free Paxton Solo app, the site management team can administer access to the premises from anywhere, via their smartphone. For the students, it means never having to remember an access code or to carry a fob, as they will simply use their phone to gain access to their building. Appropriate access permission When a smartphone with appropriate access permission is presented to a Solo controlled door, the phone communicates to the Solo controller using Bluetooth Low Energy frequency to instruct the door to open. With minimal Wi-Fi on site, the phone uses mobile data to confirm appropriate access permissions are available for that door. Where no network connectivity is available, the credential can be stored on the phone for 3-4 hours, to allow access even if the phone is offline. By running Solo alongside the existing standalone system for a period, students were migrated over to Solo in a phased approach. The access code for the legacy system was changed to prevent access via this means, once all residents were up and running with the Paxton Solo app. Existing standalone system Mike said: “As soon as we saw the Solo introduction, we knew it would be a great fit for our clients at One London Road. The premises have no network infrastructure, so a standalone system was always going to be a requirement. But with approximately 500 students on site, our clients would really benefit from more features of a centralised system.” “We know that Solo is very new, but since it’s a Paxton product, we had faith in it from day one. We know Paxton products are reliable, and if it’s needed, the Paxton team is there to support.” As a Paxton Platinum Partner, JPR Fire, Security and Data have extensive experience with Paxton products, so felt very confident in proposing an innovative solution to meet the requirements of their valued and longstanding client. Network infrastructure requirements Mike continued: “Aside from the benefit of Solo being cloud-based, with no network infrastructure requirements, the other real selling point for our customers was the price. The upfront cost of the Solo kit is very accessible. Even with the ongoing cost of the door subscription, our clients would see a cost saving compared to extending their previous standalone system, as they were constantly replacing lost fobs in significant numbers. They were immediately interested in the new system.” With the introduction of the Solo system on site, One London Road was also able to secure access to the students’ common rooms. Where previously access was available to anyone who had gained entry to the building, Solo ensures that only students in residence with appropriate access permissions can use the space by presenting their phone to the Solo DoorTag. Providing accurate information Tallulah-Mae Moran, General Manager at Homes for Students said: “Paxton’s Solo system has reduced the ongoing costs of replacing fobs and time spent doing this. The ability to see the date and time of who accessed which door is extremely useful for us and allows us to manage the site to a better standard and provides accurate information when investigating issues on site. It also allows us to set users up and manage this remotely rather than provide and collect physical fobs. It has been a worthwhile investment and will continue to be effective in years to come.” JPR Fire, Security and Data intends to continue proposing Solo as a solution for all clients who are in search of a standalone system in the future.

ZeroEyes, creators of the pioneer multi-analytics weapons detection and threat intelligence platform, announces that its proactive AI gun detection and intelligent situational awareness software has been deployed by Goessel USD 411 in Kansas to help protect students, staff, and visitors from gun-related threats. Goessel USD 411 is a small rural district serving approximately 285 students and employing 75 faculty and staff members across two campuses -- an elementary school and a combined junior-senior high school. The district is strengthened by a caring and supportive community, engaged families, and a strong school board, all of which contribute to its success and commitment to student well-being. Broader community initiatives The district secured funding through the Kansas Safe and Secure Firearm Detection Grant Program, administered by the Office of the Kansas Attorney General, to purchase and implement ZeroEyes. The grant followed coordination with local law enforcement and community leaders that identified AI gun detection as a key safety priority aligned with broader community initiatives. “I was very impressed by the system’s performance during our calibration process,” said Scott Boden, Superintendent of Goessel USD 411. “The ability to accurately detect and identify a handgun from a distance exceeded our expectations and gave us added confidence in the technology’s role in helping keep our schools safe.” Intelligent situational awareness ZeroEyes’ AI gun detection and intelligent situational awareness software layers onto existing digital security cameras. If a gun is identified, images are instantly shared with the ZeroEyes Operations Center (ZOC), the industry’s only U.S.-based, fully in-house operations center staffed 24/7/365 by specially trained U.S. military and law enforcement veterans. If the threat is determined to be valid, alerts and actionable intelligence — including visual description, gun type, and last known location — are dispatched to law enforcement and school officials, often in a matter of seconds from the moment a gun is detected. Proactive detection technology Goessel USD 411 works in coordination with county law enforcement and surrounding agencies to support school safety efforts. The addition of ZeroEyes enhances this collaboration by providing earlier detection and faster communication, helping bridge the gap created by geographic distance and limited local resources. “Goessel USD 411 is taking an important step in strengthening school safety by implementing proactive detection technology,” said Mike Lahiff, CEO and co-founder of ZeroEyes. “By leveraging grant funding to bring advanced capabilities into a rural environment, the district is demonstrating a strong commitment to protecting its students and staff while preserving the close-knit culture that defines its community.”