###### Abstract  
The Internet of Things or \"IoT\" determines the highly interconnected network of heterogeneous devices where each type of communication seems to be possible, even unauthorized. Consequently, the security requirement for these networks became crucial, while conventional Internet security protocol was identified as unusable in these types of networks, especially because of some classes of IoT devices with constrained resources. Secure group communication (SGC) in the IoT environment is vital to ensure the confidentiality, integrity, and availability (CIA) of data swapped within a collection of IoT devices. Typically, IoT devices were resource-constrained with limited memory, processing, energy, and power, which makes SGC a difficult task. This article designs a Fully Homomorphic Encryption with Optimal Key Generation Secure Group Communication (FHEOKG-SGC) technique in the IoT environment. The presented FHEOKG-SGC technique mainly focuses on the encryption and routing of data securely in the IoT environment via group communication. To accomplish this, the presented FHEOKG-SGC technique initially designs an FHE-based encryption technique to secure the data in the IoT environment. Next, the keys in the FHE technique are chosen optimally using the sine cosine algorithm (SCA). At the same time, the plum tree algorithm (PTA) is applied for the identification of the routes in the IoT network. Finally, the FHEOKG-SGC technique employs a trust model to improve the secure communication process, and the key management center is used for optimal handling of the keys. The simulation analysis of the FHEOKG-SGC technique is tested using a series of experiments, and the outcomes are studied under various measures. An extensive comparative study highlighted the improvement of the FHEOKG-SGC algorithm over other recent approaches. t 2023 1 (c) 2023 1 (c) 2023 (  
the vehicle to sense its environment and thus take the correct decision [4]. On the other hand, Vehicle-to-Vehicle communication lets two particular vehicles interchange data, in a P2P manner, regarding their position and speed. Hence, it could improve the environment, avoid crashes, and ease traffic congestion [5]. Securing the interaction between its devices has been a significant challenge faced by the IoT. It is a challenging problem since IoT gadgets have the particularity of being heterogeneous. Various contemporary scenarios necessitate communication to and data acquisition from several devices with the same functionalities [6], e.g., nodes, medical sensors, and industrial Wireless Sensor Network (WSN) nodes installed in smart homes. For this scenario, group communication has proven to be potentially one in the form of broadcasting and multicasting. In a communication network, Group Key Management (GKM) includes the updating, handling, distribution, and revocation of cryptographic keys to different group members [7]. GKM is adopted in a distributed or centralized manner. The centralized GKM technique includes a centralized entity, such as a Key Distribution Center, which performs and produces keys for the above-mentioned functions. On the other, in dispersed GKM techniques, nodes were clustered into groups and various cluster heads (CHs) were allocated to manage keys locally [8]. However, the latter method has higher computational costs; as a result, much research is based on the centralized method. Nowadays, traditional GKM methods execute ineffectually in dynamic IoT environments, i.e., those nodes often join or leave a network or migrate over a period [9]. In this scenario, if changes happen in the network, keys should be distributed and updated so that forward and backward privacy is maintained. Other than this, the overall scalability of the system can be limited by using asymmetric cryptography in dynamic IoT environments [10]. Therefore, a GKM technique based on symmetric cryptography that can effectively scale in dynamic settings was in demand.