The Growing Risk of Unmanaged IoT Devices

In today’s hyper-connected world, unmanaged IoT devices represent one of the fastest-growing security threats. Research shows that over 50% of IoT devices contain critical vulnerabilities, and one-third of all data breaches now involve an IoT endpoint. Data privacy is a major concern in IoT security, as protecting sensitive information and ensuring confidentiality is essential to prevent attacks and unauthorized access. With billions of devices being deployed across the healthcare industry, automotive, energy, and manufacturing industry, traditional security models cannot keep up.

Traditional security methods are often insufficient due to the scale and diversity of most IoT devices, which require scalable and adaptive solutions beyond legacy approaches.

The recent Eleven11Bot botnet attack highlights the risks: thousands of unsecured devices exploited in minutes, threatening enterprise networks and critical infrastructure. Many IoT devices are shipped with default passwords, making them easy targets for attackers and increasing the risk of a data breach.

As attack surfaces expand, CISOs are urgently seeking AI-powered IoT security solutions that can provide visibility, automate protection, and enforce compliance at scale.

This is where Device Authority’s KeyScaler 2025 steps in.

Understanding the IoT Ecosystem

The Internet of Things (IoT) ecosystem is a vast, interconnected web of iot devices—ranging from smart thermostats and wearable devices to industrial machines and security cameras—all communicating and exchanging data across iot networks. As the number of connected devices continues to surge, the volume of data generated grows exponentially, creating both opportunities and challenges for organizations. The iot security foundation is essential for maintaining the integrity and trustworthiness of this ecosystem, as every device represents a potential entry point for cyber threats.

Artificial intelligence and machine learning have become indispensable tools in securing the internet of things. These technologies enable organizations to monitor network traffic, detect compromised devices, and respond to malicious traffic in real time. With so many devices transmitting sensitive data, robust security solutions are required to prevent unauthorized access and data breaches. As the iot ecosystem expands, investing in advanced iot security measures is critical to protect both the devices themselves and the valuable information they handle.

What is AI and Machine Learning-Powered IoT Security?

AI-powered IoT security combines traditional cybersecurity practices with machine learning and automation to protect devices throughout their lifecycle. Unlike manual approaches, which are slow and prone to error, AI-driven systems can:

• Detect and classify unmanaged devices instantly
• Analyse behavioural patterns for anomalies
• Use deep learning and anomaly detection to detect threats in real time
• Automate certificate management and credential provisioning
• Enforce policies in real time
• Continuously adapt to new threats

AI algorithms, as a branch of computer science, analyze data from IoT devices to enhance security and proactively detect threats.

In other words, AI turns IoT security from reactive to proactive.

Introducing KeyScaler 2025

Device Authority‘s KeyScaler 2025 is the latest release of its award-winning IoT identity and access management platform. It brings together:

• AI-supported automation: Simplifies the lifecycle of unmanaged devices, from discovery to decommissioning.
• Zero Trust enforcement: Every device must authenticate before accessing the network, with robust access control measures in place.
• Policy-based control: Security is no longer manual — policies are applied consistently across thousands of endpoints.
• Compliance alignment: Built to meet the latest frameworks including NIST, the Cyber Resilience Act (CRA), and Executive Order 14028.

KeyScaler 2025 supports securing IoT by providing advanced data management and access control features, ensuring efficient handling of device data and protection against unauthorized access.

With both on-premises and KeyScaler-as-a-Service (KSaaS) deployment options, enterprises can adopt the model that best suits their digital transformation goals.

Why AI Matters for IoT Security

Traditional IoT security often struggles with scale and complexity. For example, hospitals in the healthcare industry may have tens of thousands of connected medical devices, many unmanaged and unpatched. Manually tracking, authenticating, and securing these devices is not feasible.

Traditional antivirus software, designed for standard computer networks, is often ineffective in an IoT environment due to the limited processing power of many IoT devices and the complexity of interconnected IoT systems. This highlights the need to secure IoT devices with AI-driven solutions that can adapt to the unique challenges of IoT environments.

AI-driven automation in KeyScaler 2025:

• Identifies rogue devices before they can connect.
• Predicts vulnerabilities based on usage patterns.
• Responds in real time to attempted attacks, without requiring manual intervention.
• Reduces operational costs by removing the need for manual certificate management.

This not only enhances resilience but also gives CISOs peace of mind that their IoT infrastructure is protected around the clock.

Automated Incident Response: Responding at Machine Speed

In the dynamic landscape of iot networks, threats can emerge and escalate in seconds. Automated incident response, powered by ai systems, is essential for keeping pace with the speed and scale of modern cyber threats. By leveraging machine learning algorithms, ai tools can continuously analyze network traffic, immediately identify anomalous behavior, and initiate mitigation actions without waiting for human intervention.

Cloud computing further enhances this capability, allowing ai systems to process and correlate vast amounts of data from many iot devices across distributed environments. This real-time, automated approach ensures that iot ecosystems remain resilient, as threats are detected and neutralized at machine speed. Security teams benefit by being able to focus on strategic initiatives, confident that automated incident response is safeguarding their iot devices and networks from evolving cyber threats.

Real-World Use Cases

1. Healthcare IoT: AI ensures only authorised infusion pumps, imaging systems, and wearables connect, safeguarding patient safety. Cellular networks are used to transmit data securely between devices, making it essential to protect data privacy in these IoT applications.
2. Automotive IoT: WP.29 compliance requires continuous cybersecurity — KeyScaler 2025 automates policy enforcement across connected vehicles. Smart thermostats and other smart devices in vehicles rely on secure connectivity and AI to enhance safety and comfort.
3. Smart Manufacturing: Factories with thousands of sensors benefit from automated identity provisioning and risk detection. Data analysis of collected data from sensors and other devices enables better decision making and improves operational efficiency.
4. Critical National Infrastructure (CNI): AI protects utilities, energy, and water systems from state-level cyberattacks by securing IoT devices and protecting data from advanced attacks.
5. Smart Cities: AI-powered IoT security supports smart city IoT applications by protecting smart devices, managing collected data, and enabling better decision making for urban efficiency, safety, and resource management.

Threat Intelligence: Staying Ahead of Evolving Attacks

Staying ahead of cyber threats in the IoT ecosystem requires robust threat intelligence. AI systems, supported by the IoT security foundation, play a pivotal role in gathering, analyzing, and acting on threat data. By applying machine learning algorithms to network traffic, ai tools can detect patterns indicative of emerging attacks, including sophisticated social engineering attacks and malicious traffic targeting IoT devices.

Artificial intelligence enables real-time threat detection and response, ensuring that sensitive data and connected devices are protected from both known and unknown threats. Security teams can leverage these insights to proactively strengthen defenses, adapt to new attack vectors, and maintain the security and integrity of their IoT networks. In an environment where cyber threats are constantly evolving, advanced threat intelligence is a cornerstone of effective IoT security.

Compliance Made Simple

One of the biggest challenges organisations face is meeting regulatory requirements while keeping costs under control. KeyScaler 2025 directly supports:

• NIST cybersecurity guidelines for IoT device management
• CRA (Cyber Resilience Act) requirements in the EU
• UNECE WP.29 for automotive cybersecurity
• Executive Order 14028 for supply chain and software integrity

KeyScaler 2025 also helps organisations maintain strong network security and efficient data management, supporting compliance by protecting sensitive data and ensuring secure, accessible information for AI-driven processes.

By aligning with these frameworks, enterprises can demonstrate compliance to regulators, customers, and partners with minimal friction.

IoT Security Testing and Validation: Ensuring Continuous Protection

Continuous protection of IoT devices and IoT ecosystems depends on rigorous security testing and validation. Regular assessments help security teams uncover vulnerabilities before they can be exploited, ensuring that IoT devices remain compliant with industry standards and best practices. AI systems can simulate a wide range of cyber threats, testing the resilience of both devices and IoT networks under real-world conditions.

Machine learning algorithms empower ai tools to analyze network traffic for signs of potential threats, enabling swift and effective incident response. By harnessing the power of cloud computing and artificial intelligence, organizations can automate much of the security testing and validation process, ensuring that protection is ongoing and adaptive. This proactive approach not only maintains the integrity of IoT ecosystems but also provides peace of mind that security measures are always up to date in the face of evolving cyber threats.

Quantifying the ROI of AI IoT Security

Beyond security, KeyScaler 2025 delivers measurable business value. Device Authority offers an IoT Security ROI Calculator that demonstrates how much organisations can save through automation.

Key benefits include:

• Lower total cost of ownership (TCO) for IoT security
• Reduced breach remediation costs
• Fewer resources spent on manual security tasks
• Improved uptime and operational efficiency
• AI-powered automation to improve IoT security while reducing costs

Building Towards a Zero Trust Future: Securing IoT Devices

The future of IoT security is Zero Trust. Every device, whether managed or unmanaged, must continuously prove its identity before accessing critical systems. AI and automation are no longer optional – they are essential. The integration of these two technologies, AI and IoT, is crucial for securing IoT devices, as it enables real-time threat detection, predictive maintenance, and robust protection against cyber threats.

With KeyScaler 2025, enterprises gain a future-proof IoT security platform that scales with their connected ecosystem, ensures compliance, and provides the intelligence needed to stay ahead of attackers. KeyScaler 2025 leverages an advanced AI system and explicit programming to enforce Zero Trust principles, enhancing the clarity and effectiveness of security mechanisms for IoT environments.

Conclusion: Why Choose Device Authority

Unmanaged IoT devices are no longer a hidden risk — they are a clear and present danger to every enterprise. Device Authority’s KeyScaler 2025, powered by AI automation, provides the most effective way to secure, manage, and future-proof connected devices.

Learn more about KeyScaler 2025 and how it can protect your business.