Guidance Framework for Developing IoT-Enabled Systems' Cybersecurity

Area of Science:

• Computer Science
• Cybersecurity
• Network Engineering

Background:

• Internet of Things (IoT) devices present unique security challenges due to limited resources and diverse network configurations.
• Existing security models for conventional systems are often inadequate for the specific vulnerabilities of IoT ecosystems.
• Heterogeneous network setups in IoT exacerbate security risks, requiring tailored solutions.

Purpose of the Study:

• To propose a novel framework for enhancing the security of Internet of Things (IoT) objects.
• To introduce a system for assigning differentiated Security Level Certificates (SLC) to IoT devices.
• To enable secure communication among IoT objects and with the wider internet based on their security posture.

Main Methods:

• Developed a five-phase framework: classification, mitigation guidelines, SLC assignment, communication plan, and legacy integration.
• Identified key security attributes ('security goals') relevant to IoT environments.
• Analyzed common IoT attacks to determine violated security goals for specific device types.
• Utilized a smart home as a case study to illustrate framework application.

Main Results:

• The proposed framework effectively classifies IoT objects based on their security capabilities.
• Security Level Certificates (SLC) are assigned, enabling differentiated security levels for communication.
• The framework addresses specific IoT security challenges, ensuring secure interactions within heterogeneous networks.
• Demonstrated feasibility through a smart home case study.

Conclusions:

• The novel framework provides a structured approach to securing heterogeneous Internet of Things (IoT) environments.
• Assigning Security Level Certificates (SLC) based on device capabilities is crucial for secure IoT communication.
• The proposed methodology offers a viable solution to mitigate unique IoT security vulnerabilities.