With the advancement of Large Language Models (LLMs) that is transforming and its use in many of our daily applications, our society is changing rapidly. Future wireless services will be impacted with such new technologies that require large amounts of data. Therefore, the focus is how to collect the large data and how to protect it so that we can improve the quality of life by enabling various applications, such as extended reality, brain-computer interaction, and VR/XR. These applications will have diverse performance requirements (e.g., user-defined quality of experience metrics, latency, and reliability) which will be challenging to be fulfilled by existing wireless systems. In addition, it is very important to provide security. To meet the diverse requirements of the emerging applications, the concept of secure LLMs has been recently proposed and used. The main challenge is to how to secure the data at the different IoT devices to provide Edge Computing LLMs. The latter requires the use of new computing technologies (e.g., edge computing), security related technologies (e.g., blockchain) and machine learning, to enable smart city applications. On the other hand, federated learning (FL) has provided a private platform in many of these applications to protect the data and reduce latency. These smart services/applications rely on efficient computation and communication resources. Furthermore, being able to provide adequate services using these complex systems presents enormous challenges. 

In this talk, we will present an overview of the LLM for Security, Security for LLM, and open challenges. Then, we showcase our research activities that will contribute to these efforts and advocate possible solutions using these models. We provide ways on how to use LLMs and efficiently offer better solutions to new applications (e.g., intelligent transportation, digital healthcare, extended reality applications, Industry 4.0,  haptics applications, etc.). Finally, we discuss some of our research results and future directions to support a variety of applications.