WiFi Traffic Inspection for Obscured Devices

This paper proposes a logging scheme to create read-write efficient records for network traffic metadata. Our goal is to integrate user-trust guarantees in IoT-regulated public smart spaces. This logging scheme is based on a dual log system where the auditor can analyze the log and then predict network consistency and security through log verification. The logging scheme uses two separate Authenticated Data Structures (ADS), i.e., Bloom Filters (BF) and Merkle Hash Tree (MHT). The proposed network monitoring logging scheme provides a novel approach to enhance efficiency and reduce verification costs. Network auditing is critical for assessing the security and integrity of an organization’s information systems and network infrastructure. Many devices are connected to the IoT network, and keeping track of them is challenging for system administrators. Logging the information of the devices present in the network, whether registered or non-registered, can assist auditors in easily verifying any non-registered device in the network. Detecting non-registered devices can play a crucial role where the network’s security is the priority. Auditors can audit the IoT network without knowing the device details, which preserves organizational privacy for the third-party auditor. The experiment shows results for verification latency and proof storage size as main parameters. In our experiment, verification of Log 1, which was developed using Bloom Filter, took 0.0435 seconds. Log 2 was produced using MHT and took 0.000969 seconds, while verifying using the linear algorithm took 31.159783 seconds. The linear log size is 292 MB of metadata, whereas the proposed scheme takes 1.63 kb for Log 1 and 66 bytes for Log 2. Therefore, our proposed scheme shows promising results with a novel approach.