Conversational AI threat identification at industrial internet of things

Smail B.; Meenakshi; Luis-Arias J.; Jawarneh M.; Hari Prasad P.V.; Pallathadka H. · Conversational Artificial Intelligence (2024) · DOI: 10.1002/9781394200801.ch30

Resumen

Industrial internet of things (IIoT) is bringing about the next industrial revolution, and its use in business has made it easier for people to do business from anywhere and at any time. Through machine automation and robotics, IIOT has helped the manufacturing industry. Also, most data processing and computing services in the internet of things (loT) ecosystem are done in the cloud. Because of this, the service-oriented architecture also uses the cloud to virtualize its usefulness service-oriented architecture (SOA). So, loT helps us get to Industry 4.0, which is the next generation of business and manufacturing. Also, when loT and cloud computing are used with existing industry infrastructure, they help the robust data system make new products and get good results in real time. Along with this growth, security problems are also getting worse and worse. Researchers are paying attention to how quickly cyberattacks on loT are growing. In the loT ecosystem, security is much more complex and needs to cover many different areas, such as data security, the availability of data and services, access control, and the security of physical devices. loT ecosystems can be set up as either open or closed ecosystems, so more research is needed for security deployments in both areas. Artificial intelligence and machine learning are important for attack detection and providing security solutions in IIoT. This manuscript provides an investigation of various security issues and security attacks in IIoT. A detailed study is conducted to identify all existing attacks in IIoT. These attacks are categorized on the basis of layers of loT architecture.