# Internet of Things (IoT) Technologies in Cybersecurity: Challenges and Opportunities
## 2 An Overview of Published Articles  
A critical challenge in IoT networks is the secure distribution of group keys among diverse devices with limited computing resources. Thus, researchers of a previous study developed a centralised management framework built on software-defined networking (SDN) and incorporated a modified one-way function tree (MOFT) protocol to address this. The presented approach protects against collusion attacks and achieves significant efficiency gains, reducing communication overhead by 39% compared to conventional OFT methods. The researchers validated their solution through formal security analysis, demonstrating effective collusion resistance while maintaining optimal computational efficiency [15]. To enhance the security of vehicle-to-infrastructure (V2I) communication, a new authentication method for the Internet of Vehicles has been developed. This method utilizes public key cryptography but improves efficiency by integrating Elliptic Curve Cryptography (ECC), fuzzy extractors, and Physical Unclonable Functions (PUFs), thus avoiding computationally intensive bilinear pairings. The protocol is engineered to withstand side-channel attacks and capture attempts made by the Road Side Unit (RSU). Furthermore,incorporating Diffie-Hellman values achieves perfect forward secrecy. The result is a demonstrably secure protocol, proven under the random oracle model, that offers reduced computational demands and communication overhead compared to similar authentication schemes [16]. The critical need for secure and efficient authentication protocols in underwater acoustic networks (UANs) has been addressed through novel research. UANs, which are deployed for marine resource management, have been identified as vulnerable to attacks due to energy limitations and susceptibility to capture. A lightweight authentication protocol for UANs was proposed with the objective of resisting sensor and gateway capture during attacks. Enhanced security and efficiency, compared to existing schemes, were achieved through a protocol that was developed based on Physical Unclonable Functions (PUFs) and chaotic maps. The security of the proposed protocol was formally proven in the random oracle model, and its performance was demonstrated to be suitable for the resource-constrained nature of UANs. The implications for broader IoT security have been highlighted, as the challenges faced in underwater sensor networks mirror those encountered in many resource-limited IoT devices deployed in hostile environments. The presented approach to authentication in constrained environments can be considered valuable for informing security designs across various IoT applications where devices are subjected to similar constraints and threats [17]. To address the growing security challenges in Internet of Things (IoT) networks, particularly the need for effective intrusion detection, the new Collaborative Intrusion Detection System (CIDS) has been introduced. The proposed CIDS is designed for IoT's hierarchical structure, utilising an edge-fog-cloud architecture combined with Federated Learning (FL). The research demonstrates significant advantages by training the system in a distributed manner using Federated Learning on a portion of the CICIoT2023 dataset (specifically, a labelled non-independent and identically distributed (non-IID) subset). The CIDS achieves reduced latency and lower resource usage while preserving the accuracy of intrusion detection. The study also provides a performance benchmark, showcasing that this approach leads to better results, such as shorter training times and decreased network traffic, compared with traditional, centralised learning-based intrusion detection models [18]. Due to the widespread use of IoT devices in daily and professional lives, the necessity of ensuring their security is emphasised. An automated system has been created to build a detailed database called VARIoT to address the need for better vulnerability information for IoT devices.