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The Internet of Things (IoT) presents security challenges. A new Software-Defined Networking (SDN) architecture identifies and isolates suspicious IoT devices in 4G/5G networks to prevent malware-driven attacks like Distributed Denial of Service (DDoS).

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Area of Science:

  • Computer Science
  • Network Security

Background:

  • The widespread adoption of the Internet of Things (IoT) creates a vast attack surface.
  • Many IoT devices lack the resources for robust security protocols, making them vulnerable to malware.
  • Existing 4G and 5G network designs require enhanced security mechanisms to mitigate IoT-related threats.

Purpose of the Study:

  • To propose a novel Software-Defined Networking (SDN)-based architecture for identifying and isolating compromised IoT devices.
  • To enhance the security of 4G and 5G networks against attacks originating from IoT devices.
  • To enable early threat detection and limit the impact of Distributed Denial of Service (DDoS) attacks.

Main Methods:

  • Development of an SDN-based architecture for network traffic analysis.
  • Implementation of a mechanism to identify suspicious IoT nodes based on their network behavior.
  • Redirection of suspicious traffic to a dedicated network slice for in-depth analysis.
  • Ensuring interoperability with existing 4G and 5G network deployments.

Main Results:

  • The proposed architecture effectively identifies suspicious IoT nodes.
  • Traffic from compromised devices can be isolated and analyzed without disrupting legitimate network services.
  • Early detection of potential threats, including DDoS attacks, is achieved.
  • The solution is designed for easy integration into current network infrastructures.

Conclusions:

  • The SDN-based architecture offers a viable solution for securing 4G/5G networks against IoT-related security threats.
  • Early detection and isolation of compromised IoT devices are crucial for preventing large-scale network attacks.
  • The proposed system enhances network resilience and security in the era of massive IoT deployment.