loT Nodes Integrated with Blockchain Clients
An IoT battery-powered device may be integrated directly with a blockchain client. This allows blockchain features to be embedded in IoT devices themselves for direct interaction between them. A multilevel blockchain system (MBS) is proposed by Mbarek et al.  to secure an IoT that uses mobile agents to enforce the flexibility and speed of transactions in the blockchain. Mobile agents roam throughout the network of IoT devices to aggregate useful data and generate hashed blocks of data, reducing time delays and solving other issues like scalability and synchronization. MBS consists of three hierarchical levels through which IoT devices can send their data securely: micro-level consisting of IoT devices, meso-level consisting of cluster heads, and macro-level consisting of the blockchain platform. The MBS platform is made up of four entities: the IoT device (collects and transmits data), ordering service (accepts transactions and creates blocks), endorsing peers (checks validity of smart contracts), and committing peers (runs validation). It includes meso, macro, and micro agents with different roles and locations in the architecture. Simulation is done using Hyperledger Fabric with l ,000 nodes and the end results are satisfactory in terms of energy consumption and response time.
Qian et al.  divide IoT into three parts, namely the network layer, application layer, and perception layer, and propose a security scheme for IoT using blockchain by considering the security issues in these layers. The application layer, consisting of smart homes, smart healthcare, and automatic driving, includes access and authentication control, privacy protection, and software handling. The network layer consists of low-power WANs and mobile networks. The perception layer requires security of devices, authentication, and access control and consists of IoT gateway and terminal devices. To manage the security and other issues of the IoT, blockchain-based platforms for IoT devices can be constructed along with the integration of cloud services. This structure, consisting of union nodes, IoT devices, cloud providers, and so on, communicates through high-speed links. Links between IoT and blockchain devices can be secured through authentication techniques to guarantee reliability. They have also discussed two open issues, namely identity verification and machine learning- based monitoring of abnormal network traffic.
A blockchain-based IoT structure is proposed by Wang et al.  using smart contacts, which aids users in keeping complete control over their useful data and also on how it is used by third-party clients. The given system model consists of three entities: aggregates are the users owning IoT devices who post transactions to the blockchain to publish data or grant permissions; subscribers (third parties) want to access the data posted on the blockchain by issuing transactions; and vendors are the IoT devices’ manufacturers w'ho are liable for producing official images of firmware. All these three entities are recognized through public-private key pairs when they want to communicate via the blockchain network. Aggregators store their published data in the off-chain network using content-based addressing. A hash is calculated for each data piece corresponding to the address of the data, which is used as an index for data search and retrieval. Two smart contracts, namely firmware update and access control, are introduced for controlling updates and providing access permissions. This blockchain-based update scheme of firmware ensures that the IoT devices are not tampered with and are designed through authentic firmware.
Another hierarchical structure of blockchain for tamper-proof storage and retrieval of data in IoT systems is discussed by Angin et al. . In this architecture, along with the resource-constrained IoT nodes, some additional devices are used for “data collection” w'hich have more storage and computational power. This model ensures that the data is sent securely to the edge servers through the resource-constrained devices for data verification. An authentication and access control method for IoT is proposed by Ourad et al.  based on a distinct blockchain-dependent architecture. The authentication process is performed through smart contracts. If found valid, the sender’s address and access token are broadcast by the smart contract through which the user can receive this information. A package is then crafted by the user and signed using the Ethereum private key. The authors have shown that this method outperforms existing methods in terms of decentralization and tamper-proof records. This approach can also withstand attacks attempted to guess credentials through brute force and control legitimate sessions.
Bubbles of trust  is an authentication method for IoT devices based on public blockchains and smart contracts. In this approach, secure virtual zones called bubbles of trust are created where each device trusts only the devices within its zone. Each zone is inaccessible and protected from non-member devices. Communications in this network are through transactions validated by the blockchain. In the initialization phase, a master device that owns a public-private key pair is designated. All objects within the system are called followers. Each follower is given a ticket that contains an objectID (identifier of follower), groupID (identifier of object’s bubble), pubAddr (public address of follower), and a signature. The master of the bubble initiates a transaction containing the identifier of the master and the group created. This transaction is validated by the blockchain to check the uniqueness of identifiers. After the creation of a bubble, the followers send transactions to get linked to their bubble. The follower’s identifier is also verified and validated by the blockchain using smart contracts. This approach satisfies the requirements of IoT in terms of its security, cost, and efficiency when implemented using Ethereum and C++ language.