Abstract
In modern information technology, the reliability and security of wireless sensor network infrastructure are particularly important. Cyberattacks such as Wormhole can significantly impact the data exchange process, reduce network performance, and lead to information distortion. Therefore, it is essential to use multi-criteria decision-making (MCDM) methods to assess the effectiveness of security measures for wireless sensor networks. In this paper, the SAW and TOPSIS methods were applied as decision- support tools in wireless sensor network security. Within the proposed research, these methods were used to evaluate three different states of a wireless sensor network: before an attack, after an attack, and after the implementation of protective measures. The evaluation was conducted based on six key criteria: temperature, pressure, humidity, bandwidth, latency, and detection accuracy. A comparative analysis of the methods was carried out, considering their accuracy and application efficiency. The experimental results demonstrated that SAW and TOPSIS are the most effective methods as they provide clear results based on predefined values and weight coefficients and allow for a precise distinction between attacks and security measures. According to the SAW method, the post-attack indicators were A = 0.587, and after implementing security measures, the system approached its pre-attack state: A = 0.831 < 0.850. The analysis using the TOPSIS method confirmed that, compared to an unprotected system, the network’s resilience to attacks significantly improved.