Method for Detecting Manipulated Compilation of Sensing Reports in Wireless Sensor Networks

Area of Science:

• Computer Science
• Network Security
• Wireless Sensor Networks

Background:

• Cluster-based wireless sensor networks (WSNs) are vulnerable to manipulated compilation attacks (MCAs).
• Malicious adversaries can compromise cluster heads (CHs) to inject false message authentication codes into legitimate reports.
• Existing security solutions fail against MCAs because they assume CHs are uncompromised, leading to the rejection of real event data.

Purpose of the Study:

• To propose a novel method for detecting manipulated compilation attacks (MCAs) in cluster-based WSNs.
• To ensure the reliable reporting of real events even when cluster heads are compromised.
• To enhance the security and integrity of data transmission in WSNs.

Main Methods:

• A collaborative report generation and verification mechanism is introduced among cluster nodes.
• The method utilizes very loose synchronization among cluster nodes for report verification.
• Upon detecting an MCA, a cluster node can immediately reforward a legitimate report.

Main Results:

• The proposed method effectively detects MCAs in cluster-based WSNs.
• Legitimate reports are successfully reforwarded, ensuring real events are communicated.
• Analytical and experimental results validate the performance of the proposed detection method.

Conclusions:

• The developed method provides a robust defense against manipulated compilation attacks in WSNs.
• Collaborative verification by cluster nodes ensures data integrity and availability.
• This approach significantly improves the reliability of event reporting in compromised WSN environments.