Recently, the Internet of Things (IoT) has gained tremendous popularity in several realms such as smart cities, healthcare, industrial automation, etc. IoT networks are increasing rapidly, containing heterogeneous devices that offer easy and user-friendly services via the internet. With the big shift to IoT technology, the security of IoT networks has become a primary concern, especially with the lack of intrinsic security mechanisms regarding the limited capabilities of IoT devices. Therefore, many studies have been interested in enhancing the security of IoT networks. IoT networks need a scalable, decentralized, and adaptive defense system. Although the area of development provides advanced security solutions using AI and Blockchain, there is no systematic and comprehensive study talking about the convergence between AI and Blockchain to secure IoT networks. In this paper, we focus on reviewing and comparing recent studies that have been proposed for detecting cybersecurity attacks in IoT environments. This paper address three research questions and highlights the research gaps and future directions. This paper aims to increase the knowledge base for enhancing IoT security, recommend future research, and suggest directions for future research.

Nowadays, the Internet of Things (IoT) has become immensely popular in various fields like healthcare, smart cities, and industrial automation. IoT networks are expanding rapidly, including different IoT devices with limited capabilities in terms of power and storage which make the IoT security a crucial issue. IoT Network Intrusion Detection System is one of the most famous solutions that used to identify different types of attack and extract their features (e.g. IP addresses of attackers). The IP address is a valuable feature that can identify malicious traffic of an attacker who attempts to access the IoT network. However, IoT Network Intrusion Detection Systems has different limitations: centralization and scalability which easily allow attackers to access the IoT network. Accordingly, this paper aims to address these issues by proposing a novel collaborative framework called Blockchain-based Collaborative Intrusion Detection Systems (BC-IDSs) that utilizes Blockchain technology to connect several IDSs. The BC-IDSs framework (1) creates a list of malicious IP addresses using IDSs; (2) utilizes Blockchain to share and store the Blacklist; (3) creates a function for duplication check in the Blockchain layer. Further, the implementation of a proof of concept for BC-IDSs framework is presented by using Ethereum Blockchain simulators. Compared to previous works, this paper discusses several types of performance metrics that prove BC-IDSs is able to secure IoT networks. BC-IDSs also increases the scalability by 50% when compared to one of the previous defence work.