Abstract: Wireless communication technologies have become an essential component of modern digital infrastructure, enabling seamless connectivity for individuals, organizations, and smart devices. WiFi networks are widely used in homes, campuses, enterprises, and public environments due to their convenience and accessibility. However, the rapid expansion of wireless networks has also introduced significant cybersecurity challenges. One of the most common threats is WiFi spoofing, where attackers create rogue access points that imitate legitimate networks in order to deceive users and intercept sensitive information.

WiFi spoofing attacks typically involve the duplication of network identifiers such as SSID (Service Set Identifier) and the manipulation of BSSID (MAC addresses). These attacks allow malicious actors to perform activities such as man-in-the-middle attacks, credential theft, data interception, and network monitoring. Traditional wireless security mechanisms such as WPA2 or WPA3 encryption primarily focus on securing data transmission but often lack effective mechanisms for detecting spoofed access points operating within close proximity.

To address these challenges, this research proposes a WiFi Spoof Detection System using IoT (ESP32). The proposed system uses ESP32 microcontrollers to continuously monitor nearby wireless networks and collect parameters including SSID, BSSID, RSSI (signal strength), and channel information. The system analyzes these parameters to identify suspicious patterns such as duplicate SSIDs with different MAC addresses or abnormal signal strength variations.

The system integrates IoT hardware monitoring, backend data processing using Python Django, and a PostgreSQL database for centralized storage and analysis. Additionally, a React + Vite.js frontend dashboard provides administrators with real-time monitoring capabilities, enabling visualization of network activities and detection alerts. Experimental implementation demonstrates that the proposed solution provides a low-cost, scalable, and efficient method for detecting rogue access points and strengthening wireless security in smart environments.

Keywords: WiFi Spoofing, ESP32, IoT Security, Rogue Access Point Detection, MAC Address Analysis, RSSI Monitoring, Wireless Intrusion Detection, Cybersecurity, Network Monitoring.

Downloads: | DOI: 10.17148/IARJSET.2026.13324