Blockchaintechnologyisanemergingandrapidlygrowingtechnologyinthecurrentworldscenario.Itisacollectionofrecordsconnectedthroughcryptography.Theyplayavitalroleinsmartcontracts.

Blockchain technology is an emerging and rapidly growing technology in the current world scenario. It is a collection of records connected through cryptography. They play a vital role in smart contracts. Smart contracts are present in blockchains which are self-controlled and trustable. It can be integrated across various domains like healthcare, finance, self-sovereign identity, governance, logistics management and home care, etc. The purpose of this article is to analyze the various use cases of smart contracts in different domains and come up with a model which may be used in the future. Subsequently, a detailed description of a smart contract and blockchain is provided. Next, different case-studies related to five different domains is discussed with the help of use case diagrams. Finally, a solution for natural disaster management has been proposed by integrating smart contract, digital identity, policies and blockchain technologies, which can be used effectively for providing relief to victims during times of natural disaster.

Inspired computing is based on biomimcry of natural occurrences. It is a discipline in which problems are solved using computer models which derive their abstractions from real-world living organisms and their social behavior. It is a branch of machine learning that is very closely related to artificial intelligence. This form of computing can be effectively used for data security, feature extraction, etc. It can easily be integrated with different areas such as big data, IoT, cloud computing, edge computing, and fog computing for data security. The chapter discusses some of the most popular biologically-inspired computation algorithms which can be used to create secured framework for data security in big data like ant colony optimization, artificial bee colony, bacterial foraging optimization to name a few. Explanation of these algorithms and scope of its application are given. Furthermore, case studies are presented to help the reader understand the application of these techniques for security in big data.