Cyber Security Embedded into Devices and Machines
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セキュリティ

The cyber-security landscape is changing….daily. Rapid detection and mitigation of a cyber-attack can mean the difference between a minor disruption or an operational catastrophe. Threat Detection in minutes instead of days.

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The Escalating Threat

Every industry that depends on the secure performance of IT and OT assets faces an increasingly complex and hazardous cyber landscape. Current problems include:

  • Overwhelming Volume

    Global cyber-attacks are increasing at a rate of ~ 300% year over year. The sheer volume of attacks overwhelms the personnel and existing tools responsible for cyber protection.

  • Device Power/Memory Limitations

    Many IT and OT edge devices operate on low power and limited memory. These devices are less adaptable to traditional security measures and more vulnerable to attack.

  • Inconsistent Connectivity

    Many IT and OT asset ecosystems contain devices and machines that have inconsistent connectivity. Connectivity disruptions increase the risk of cyber intrusion.

  • Inability to Predict Threats

    Most legacy security tools are purely reactive. Asset stakeholders have no ability to predict potential cyber threats or to take preventive action.

  • Crippling Ransomware Attacks

    Ransomware attacks can result in the temporary or permanent loss of sensitive data. Depending on the scope of the attack, a single asset, an entire factory, or a chain of interconnected factories can be disabled.

  • High Cost of Data Processing

    Heavy reliance on cloud-based data processing adds significant cost to security programs. Configuration costs can also be prohibitive.

An Arsenal of IT and OT Security

MicroAI™ has pioneered the latest in Edge-native AI technology to develop products that bring powerful cyber-security capabilities to IT and OT infrastructures.

MicroAI Security™ – A More Local Approach to Cyber-Security

Monitoring, alerting, and mitigation at the asset endpoint Edge-native AI for Next-Generation Zero-Day Attack Protection

  • Machine and device

    Machine and device centric:

    MicroAI Security™ is embedded at the MCU or MPU of a device or machine – Zero-Day protection at the extreme edge.

  • Proprietary algorithms

    Proprietary algorithms:

    Predictive AI and ML algorithms that live, train, and learn directly on the targeted asset – predict instead of reacting.

  • Quicker alerts

    Quicker alerts & faster mitigation:

    Endpoint security that enables quicker detection and reaction to Zero-Day infections – staying one step ahead of hackers.

  • data-processing

    Local monitoring & data-processing:

    Processing critical data at the endpoint eliminates security risks associated with cloud processing – more secure and more cost effective.

MicroAI AtomML™ and AtomML+™

Embedded (AtomML) and Edge (AtomML+) security that lives, trains, and monitors asset security either at the individual asset microcontroller (MCU) level or at the edge (depending on application).

  • Reduced Cloud Dependence

    Edge-native security allows all critical data to be collected, synthesized, and analyzed locally. Critical IT edge device data is not exposed to cloud transmission, significantly reducing its exposure to cyber-attack.

  • Personalized Security

    Ability to customize security protocols on a device-by-device level to accommodate specific conditions for individual devices or groups of devices.

  • Quicker Alerts and Mitigation

    Localized, device-specific, security that provides quicker notification of security breach and faster activation of mitigation actions.

  • Predictive Security

    Predictive analytics produce actionable insights into future threats. Enables a transition from reactive to predictive security.

  • Simple Integration

    Quickly onboard and validate security protocols into devices within the IT ecosystem. Eliminates the need for expensive external hardware and costly data labeling.

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The Internet of Things is digitally transforming all industries.

MicroAI Launchpad™

Launchpad provides a comprehensive platform for development, test, deployment, and visualization of machine learning-enabled cyber-security capabilities.

  • Access to MicroAI Library

    Developers can quickly access and onboard MicroAI’s AI and ML software libraries and SDKs.

  • Live Data Ingestion

    Seamless and secure ingestion of data from a wide variety of IT and OT devices and machines (sensors, robots, field assets, network equipment, etc.).

  • インテリジェントなワークフロー

    The embedding and training of intelligent workflows that automate the process of security alert notifications and implementation of rapid threat mitigations.

  • Real-time Visualization

    A centralized visualization engine that provides continuous visualization into the security status of connected devices and machines.

  • Live Testing and Iteration

    Developers can easily test their initial designs within a controlled, real-time, environment. Design iterations can be quickly implemented and validated.

Operational Benefits

  • Cyber-security that protects against the most sophisticated cyber-attacks (Zero-Day, Ransomware, DDoS, etc.)
  • AI-enabled evolution from a reactive to a predictive cyber-security state
  • Reduced risk of negative financial impacts resulting from data theft and/or operational disruptions
  • Low implementation cost and reduced management burden
  • Dynamic security that evolves with the changing threat landscape (protection for today and tomorrow)
Operational-Benefits

Interested in how MicroAI can benefit you?

 MicroAI AtomML brings big infrastructure intelligence down into a single piece of equipment or device.

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