Sistema de seguridad inteligente para monitoreo de ataques en una WSN para ambientes de agricultura de precisión.

Abstract

In precision agriculture, ensuring the security of wireless sensor networks (WSN) is essential to maintain soil data integrity and optimize agricultural productivity. This project develops an intelligent system to detect cyber attacks targeting such networks, including DoS or denial of service attacks and data injection, and mitigate their impact. To achieve this, the ESP-NOW protocol, used by our client’s WSN, and the traffic between ESP8266 devices were analyzed to determine features that can predict DoS attacks. Security measures were implemented, such as an access list based on authorized MAC addresses and message validation using HMAC-SHA256. A microcontroller configured as a sniffer captured and analyzed network traffic, enabling the development of a detection model. This process involved data collection, preprocessing, feature selection, training, and validation using both collected datasets and live traffic. The results show that the model accurately classifies network traffic destined for the receiving node, distinguishing between normal traffic and DoS attacks with 99.9% precision under specific conditions. This approach enhances the security and reliability of WSNs in agricultural environments, encouraging their adoption by ensuring data integrity and supporting decisions based on accurate information. Keywords: WSN, Network Attacks, Precision Agriculture, Artificial Intelligence, ESP-NOW