Navegando por Autor "SILVA JÚNIOR, Walter Claudino da"

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Sistema unificado de detecção e mitigação de ataques de Evil Twin em redes Wi-Fi industriais com IoT/IIoT
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) SILVA JÚNIOR, Walter Claudino da; NASCIMENTO, Manoel Henrique Rei
The security of Wi-Fi networks in industrial environments has become a critical challenge in the context of digital transformation, especially with the widespread adoption of IoT and IIoT devices. The Evil Twin attack, characterized by fraudulent access points impersonating legitimate networks, poses a serious threat to the confidentiality, integrity, and availability of industrial systems. Traditional protocols such as WPA2-PSK prove insufficient in complex environments, leaving networks vulnerable to data interception and unplanned production downtime. This dissertation proposes a Unified Detection and Mitigation System (UDMS), integrating robust RADIUS-based authentication (IEEE 802.1X), continuous monitoring through the Snort intrusion detection system, and centralized access management via Active Directory. The methodology involved progressive implementation across five experimental scenarios with controlled attack simulations. Results showed a reduction in attack success rate from 87% to less than 10%, maintaining latency below 400 ms and achieving high accuracy with low false positive and false negative rates. The study concludes that the integrated approach outperforms conventional solutions, providing effective and viable protection for industrial Wi-Fi networks.
Unified System for Detecting and Mitigating Evil Twin Attacks on Industrial Wi-Fi Networks with IoT/IIoT
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) SILVA JÚNIOR, Walter Claudino da; NASCIMENTO, Manoel Henrique Reis
Wi-Fi network security in industrial environments has become a critical challenge in the era of digital transformation, especially with the widespread adoption of IoT and IIoT devices. The Evil Twin attack, which creates fraudulent access points identical to legitimate ones, poses a serious threat to confidentiality and availability in industrial systems. This study proposes a Unified Detection and Mitigation System (UDMS) that integrates RADIUS-based robust authentication, continuous monitoring using Snort intrusion detection system, and centralized access management via Active Directory. Tested in five progressive scenarios, the system reduced attack success rates from 87% (WPA2-PSK) to just 2%, while maintaining latency below 400ms, with low false positive (6%) and false negative (3%) rates. The research provides a practical framework for securing industrial Wi-Fi networks without compromising operational performance.