Attack Classification Schema for Smart City WSNs

Area of Science:

• Computer Science
• Network Security
• Urban Technology

Background:

• Wireless Sensor Networks (WSNs) are increasingly deployed in urban areas for smart city initiatives.
• The reliability of WSNs is crucial for municipal services, but they are vulnerable to various cyberattacks.
• Existing WSN security measures are inadequate for the complex, multi-provider environment of smart cities.

Purpose of the Study:

• To address the security challenges of WSNs in smart cities.
• To propose a novel intrusion detection framework tailored for smart city environments.
• To introduce an attack classification schema for identifying and categorizing WSN threats.

Main Methods:

• Development of a new intrusion detection framework for WSNs.
• Creation of a classification schema for WSN attacks in smart cities.
• Simulation of a selective forwarding attack on parking and sound WSNs to demonstrate the framework's efficacy.

Main Results:

• The proposed framework and classification schema can help administrators identify plausible attacks.
• The system can pinpoint affected components and providers within the smart city infrastructure.
• Proof-of-concept demonstrated successful detection and classification of a simulated attack.

Conclusions:

• A new security perspective is essential for WSNs in smart cities.
• The proposed framework and schema enhance the security and reliability of WSNs for urban data collection.
• This approach supports smart city administrators in managing WSN security incidents effectively.