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| Title | Securing The Internet Of Things (Iot) Environment Using Bio- Inspired Meta-Heuristic Methodologies |
|---|---|
| ID_Doc | 47805 |
| Authors | Harikrishna P.; Kaviarasan R.; Kalaiyarasan R. |
| Year | 2024 |
| Published | AI and IoT Technology and Applications for Smart Healthcare Systems |
| DOI | http://dx.doi.org/10.1201/9781032686745-22 |
| Abstract | In the present digital era, the Internet of Things (IoT) has gained significant traction in the divergent fields of constructing smart cities, agriculture, medicine, handheld devices and traffic monitoring systems. IoT has been used to inculcate objects with intelligence in order to deceive, recognize and assist the machines and humans present in the environment. In the present IoT network, many physical entities like humans and devices have been connected. When the network scales up, there will be a huge rise in volume, velocity and different types of data generated from the connected devices in the network. Due to the environmental and dynamic factors of IoT systems present in the network, designing a secure and robust IoT network becomes a hectic problem for researchers. Privacy, medical and government data will be at a very high security risk. On conducting a literature survey and based on the analysis, there have been potential drawbacks to the methodologies present, and it is quite evident that meta-heuristic approaches are more suitable for designing a robust IoT network. The meta-heuristic algorithms are bio-inspired, mimicking the behavior of the species, and they have promising results in the search space deployed. It is also problem-independent, and irrespective of the problems, it can be applied and always attains global optimization. The proposed system HECB_OA is compared with other benchmark systems like SFLA, ITACS and BPSO_BGWO. © 2024 selection and editorial matter, Alex Khang. |
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