Network Scan Failure and Delay Estimation of IoT Wireless Equipment using Scenario Detection Technique

This paper proposes a method of identifying the scan response state based on a similarity measure between scan response preliminary obtained in various network states and an unknown scan response data in order to estimate the cause of network scan failure/delay which is necessary in detecting compromised IoT wireless devices. Existing methods for measuring similarity between two vectors fail to find similarity between two scan response data where the distribution, dimension, or magnitude of such scan response data differs, therefore, a method that can clearly measure the similarity between scan responses data is required. In particular, a similarity measure based on the average absolute deviation with a baseline scheme that can be utilized for easy identification of the network scan response scenario is proposed. Thereafter, the estimation of cause of scan failure/delay is presented. The goal of our proposed method is to detect early the state of the target (scanned) network, in order to accurately estimate the cause of scan failure/delay from the scan response data. The performance of the proposed method is evaluated using computer simulation. The evaluation results show that the proposed similarity measure achieved high similarity ratio of all unknown scan response samples to correct scenario and outperforms other conventional similarity measure methods. Also, it is confirmed that the cause of scan failure/delay could be estimated with over 90% correct estimation accuracy in various scenarios.