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The Internet of Things (IoT) is a quite recent technology that has emerged in recent years. It enables the progression of a diverse wide variety of new venture application options (e.g., wearables, smart homes, smart cities, etc.). However, there are issues with IoT security measures that must be handled in order to maintain a secure connection. In recent years, distributed denial of service (DDOS) attacks has emerged as significant danger to the Internet of Things network. DDoS attacks deplete the resources available to IoT end devices, such as storage and network bandwidth, resulting in difficulties with IoT applications. This study’s goal is to develop an effective DDoS detection framework for IoT environments in the fog layer. The framework uses two types of techniques to deal with both known and unknown attacks. They are signature-based and machine learning-based anomaly detection techniques. Fog computing enables the mitigation framework to be resource efficient.
Dave et al. (Thu,) studied this question.
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