Adaptive Intrusion Detection Systems

Adaptive Intrusion Detection Systems

Topic:    Enhancing Security in Internet of Things (IoT) Networks through Adaptive Intrusion Detection Systems

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Adaptive Intrusion Detection Systems

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APA

Adaptive Intrusion Detection Systems

Introduction

The Internet of Things (IoT) connects billions of devices, creating vulnerabilities that demand robust security solutions like adaptive intrusion detection systems (IDS). This paper explores how adaptive IDS enhance IoT network security, addressing challenges, technologies, and future directions at Southern Wellness Care LLC, a hypothetical health clinic deploying IoT for patient monitoring.

Background and Significance

  • Overview of IoT growth, with 15.9 billion connected devices in 2025 (Statista, 2025).

  • Importance of security in IoT due to 2.6 billion data breaches in 2024 (Imperva, 2025).

  • Role of adaptive IDS in dynamically countering evolving threats.

Purpose and Scope

  • Examine adaptive IDS as a solution for IoT security.

  • Focus on healthcare IoT applications, like patient monitoring systems.

  • Outline technical, ethical, and implementation considerations.

IoT Security Challenges

IoT networks face unique security threats due to their scale, heterogeneity, and resource constraints, necessitating adaptive IDS to mitigate risks.

Vulnerability Landscape

  • Common threats: DDoS attacks (60% of IoT incidents), malware, and unauthorized access (Splunk, 2024).

  • Device constraints: Limited processing power and

    • battery life hinder traditional security.

    Impact on Healthcare IoT

    • Risks to patient data privacy under HIPAA, with 70% of IoT devices vulnerable to breaches (Bhatt et al., 2023).

    • Case study: Ransomware attacks on healthcare IoT, costing $1.2 million per incident (Imperva, 2025).

    Adaptive Intrusion Detection Systems

    Adaptive IDS leverage machine learning and real-time analytics to detect and respond to IoT threats dynamically, offering a proactive security approach.

    Core Components and Functionality

    • Anomaly detection using machine learning models (e.g., neural networks).

    • Real-time monitoring and response, reducing detection time by 40% (Bhatt et al., 2023).

    Types of Adaptive IDS

    • Host-based IDS for individual IoT devices.

    • Network-based IDS for monitoring traffic patterns, effective against 80% of…

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