To enable digital cities and provide autonomous driving experiences, intelligent transportation systems (ITS) are deployed. This technique imparts vigorous features because of the quick mobility of nodes. Real-time data security and privacy are the most important and underappreciated preconditions in vehicular communication. The functionality of a wireless network should be dispersed over several automobiles/infrastructure, such as processing capability in fog, edge, and cloud servers, to reduce latency and increase service quality (QoS). In the past, several mathematical methods have been utilized to tackle optimality problems. This chapter analyzes multi-access edge and fog computing techniques for the security and privacy of a 6G-driven vehicular communication network in the internet-of-everything (IoE) Industry 5.0. It also includes a summary of 6G research directions as well as a number of potential 6G communication applications along with dark web crimes.
TopIntroduction
The advanced and latest crime phenomenon occured in the criminal law enforcement is the use of dark web for crimes. The offence of deploying the Dark web is a that threatens the society should be penalized by the criminal law. Using wireless connection and various gadgets to execute any crimes is the fundamental sign that this type of crime is different from other types of crime.
Sixth-generation (6G) communication networks have recently been deployed and have integrated a variety of technologies, including sensitive sensors, automated vehicles, mesmeric multi-media, and Dark web of Things (IoT) technologies. Many transmission nodes and endpoints are required for such sophisticated approaches. Furthermore, these technologies face a number of hurdles, including scarcity in any connected network and numerous challenges relating to each node privacy and security. The main idea behind implementing a 6G network is to merge the physical and digital worlds in all aspects. Furthermore, the coming epoch will be defined by automation. Almost all computations will be performed on the system rather than over the network. As a result, the intelligent network must be synchronised across all nodes.
Maintaining reliable connection between numerous wireless components mounted on a vehicle or along a nearby road. Additionally, offering technical assistance for a variety of new apps and approaches that are appropriate for an automated environment in 2030 and beyond. However, the most significant challenges in adopting a 6G network environment are the processing of information in bulk, the management of bulky information, and the implementation of large amounts of data.
Intelligence Edge Computing (IEC) is an advancement of existing cloud computing techniques that enables easy access to a variety of users. IEC is a technology specified by the European Telecommunications Standards Institute (ETSI) that may make wireless connections and connect to various cloud resources. Industry Specification Group (ISG) used IEC in addition to ETSI to improve the storage and processing speed at the network's edge. In addition, IEC provides mobile vehicles with portability and wireless connection, allowing them to send and receive vital messages at any time and in any area. Email, fax, file transfer, and other types of messages can be sent over a wireless network. Bluetooth, cellular networks, satellite communication systems, and other networks are utilised to convey these messages in a dynamic environment. IEC technology is designed to reduce bandwidth, reaction time, and implementation costs, among other things.
As the effectiveness of a network improves, the network's complexities grow. 6G gigantic network IoT faces numerous issues which which are discussed in Figure 1.
To overcome all of the abovementioned obstacles, the massive IoT will have to rely on a variety of clever learning techniques as well as the precise use of Fog and Edge computing devices located near the vehicle. By offloading computations from the cloud machine and performing them on the edge computing device, fog computing and edge computing devices reduce computation latency. To boost network efficiency, fog devices will intelligently combine idle/spare resources from all available devices. Fog devices, edge devices, and other available devices' computational resources will be critical in addressing the demands of highly demanding future applications. Devices can offload tasks and cache data to fog nodes by establishing multiple fog nodes at various locations. When compared to the centralised computing supplied by the cloud, one of the key advantages of fog computing is the decentralised computing service. Moreover, improved latency is achieved as data and tasks are accessed and analyzed near to the end devices. Fog computing also improves the usage of frequency spectrum and enhances the network capacity. It also has positive impact on application reliability as computation and storage capabilities are strengthened by the placement of fog nodes.