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The Internet of Things (IoT) and the Industrial Internet of Things (IIoT) have grown significantly in the last decade, underlining the increasing need for effective, secure, and reliable data communication protocols. The widely accepted Message Queuing Telemetry Transport (MQTT) protocol, with its structure that meets the needs of welding-oriented devices in IoT and IIoT applications, is a prime example. However, its user-friendly simplicity also makes it susceptible to threats such as Dispersed Services Rejection (DDOS), Brete-Force, and incorrectly shaped package attacks. This article introduces a robust and reliable framework for preventing and defending against such attacks in MQTT-based IIoT systems based on the theory of merging attacks. The expert system incorporates the Adaboost model and can detect anomalies by processing network traffic in a closed setting and identifying impending threats. With its robust design, the system was subjected to various attack scenarios during testing, and it consistently detected interventions with an average accuracy of 92.7%, demonstrating its potential for use in intervention detection systems. The research findings not only contribute to the theoretical and practical concerns about the effective protection of IIoT systems but also offer hope for the future of cybersecurity in these systems.

The rapid transition of all areas of our lives to the digital environment has kept people away from their intertwined social lives and made them dependent on the isolated cyber environment. This dependency has led to increased cyber threats and, subsequently, cyber-attacks nationally or internationally. Due to the high cost of cybersecurity systems and the expert nature of these systems' management, the cybersecurity component has been mostly ignored, especially in small and medium-sized organizations. In this context, a holistic cybersecurity architecture is designed in which fully open source and free software and hardware-based Raspberry Pi devices with low-cost embedded operating systems are used as a honeypot. In addition, the architectural structure has an integrated, flexible, and easily configurable end-to-end security approach. It is suitable for different platforms by creating end-user screens with personalized software for network security guards and system administrators.

İnsanlık tarihi teknolojik açıdan önemli aşamalardan geçmiştir ve geçmeye devam etmektedir. Bu aşamaların en önemlilerinden birisi de Endüstri 4.0 sürecidir. Bu süreçle birlikte geleneksel sanayi üretimi yerini bilişim sistemlerinin ön planda olduğu bir yaklaşıma bırakmıştır. Endüstriyel haberleşme sistemleri ilk üretildikleri zamanlarda tamamen izole olarak yönetilmişlerdir. Zamanla iç ağlara (intranet) devamında ise internete bağlanmaları ile Endüstri 4.0 süreci başlamıştır. Bu süreçte siber-fiziksel sistemlerin ortaya çıkmasıyla birlikte, bu sistemler siber tehditlere karşı açık hale gelmişlerdir. Bu zafiyetler akıllı sistemleri ve Endüstri 4.0 sistemlerini saldırganların gözdesi haline getirmiştir. Her ne kadar bu sistemler verimlilik, sürat, işlerlik gibi insan hayatına önemli katkılar sağlasa da siber güvenlik açıklıkları uygun şekilde değerlendirilmezse, Endüstri 4.0'ın gerçek potansiyeline asla ulaşılamayabilir. Bu nedenle, çalışmada Endüstri 4.0’ın tüm bileşenleri ele alınarak, Siber Güvenlik bileşeni üzerine odaklanılmıştır. Çalışma, Endüstri 4.0’ın siber güvenlik boyutuna yönelik çalışmalara önemli katkı sağlayacaktır.

IoT devices, which are increasing in highly manner day by day, are now in everywhere in our life. WSNs are used together with IoT devices to monitor real environments. In this study, attacks against WSNs were carried out. The attack chosen for this study is a flood attack. In addition, solution suggestions for this attack are presented. In this context, firstly reference and attack packages have been collected, and then the collected packages have been compared with the reference packages and forensic investigations have been carried out. The result of the evaluation has shown the importance continuous monitoring on 24/7 basis and detecting abnormal behaviors in IoT traffic with forensics analysis for preventing attacks.