The Internet of Things (IoT) is a series of recording devices, mechanical and automated machines, documents, creatures, or individuals that have one of the user identifiers and the ability to substitute information over a network without requiring human-to-human connections. The IoT technology is used in different applications to transfer information between two or more stations or devices using actuators/sensors. The IoT has many fields of application, including smart home, healthcare, transport and logistics, and industry. Each application gives highlights and important and explicit administrations. This paper provides an overview of IoT applications, discussing their current problems and potential challenges. In addition, it focuses on issues and challenges that arise for future IoT systems including enormous scaling, planning and needs, generating information and big data, strength, frankness, resource management, privacy, and security. The secure data transformation is more problematic in ongoing research. So, this survey presents security attacks and different security mechanisms involved in IoT applications including authentication, encryption, blockchain, and trust management. Blockchain with IoT applications provides good secure data transfer compared to other security mechanisms. So, this survey mainly concentrates on the blockchain with IoT applications and its latest issues. The objective of this paper is to analyze the issues and challenges of IoT applications, eight research topics in existing systems, security attacks and their countermeasures, and different security mechanisms confronting the IoT.
Cloud computing is breakthrough technology with applications in education, industry and research. Implementing a cloud environment, however, depends on virtualization, parallel computing, resource management, service-oriented architecture, and distributed computing. The efficiency of cloud computing depends on effective resource allocation (RA). Conventional RA, from resource requests to price settlement, is handled entirely by cloud service providers (CSPs), which make it difficult for end users (EUs) to view details relating to resource availability and price. Hence, an alternative technique is required to provide an efficient RA between EU's. In this work, the blockchain (BC) technique is used for RA between the EU's without the intervention of CSP. The BC provides decentralized and secured communication between the EU's without any inconsistency. Based on demand, RA is carried out in two different ways, fixed size and variable size. In a fixed size RA, each user utilizes an equal quantity of resources at a particular time but in a variable size RA each user utilizes the varying quantity of resources based on demand. Given that the RA, chosen depends on resource availability and demand, the proposed work employs hybrid RA (Adaptive Resource Allocation) schemes such as fixed-size adaptive RA (FSARA) and variable-sized adaptive RA (VSARA). The simulation results show the comparative analysis of the proposed and existing RA techniques. When compared to existing RA techniques like optimal, greedy and iterative techniques, the proposed technique HIGHLIGHTS• The permissioned blockchain is used for resource allocation and monitoring.• To reduce storage size, partial data is stored in the onchain blocks instead of entire data.• The EU's based Fixed and variable size resource allocation techniques are proposed.
Nowadays, improving a crop yield ([Formula: see text]) is an emerging and essential task to reduce food scarcity. Factors impacting [Formula: see text] improvement include rising population, water shortage, fertilizer use, climate change and unprecedented insect attacks. To resolve these issues, a smart agriculture technique is proposed in this work. Internet of Things (IoT) sensor devices are used to collect data from farms, following which the fuzzy association rule-based classification technique classifies the data into two, valuable and nonvaluable. An improved artificial neural network (IANN) algorithm is applied to identify and analyze the factors involved in monitoring [Formula: see text]’s. Thereafter, all valuable data pertaining to the type of seed, fertilizer and crop cost is stored in blocks to secure data and communication between members of the farming community. Finally, an edge computing device is used to store the blocks and transfer information. The valuable data collected is classified using the fuzzy association rule and analyzed using the IANN technique, both of which facilitate a comparison with the historical data so as to enable better decision making in terms of seed and fertilizer selection. Similarly, crop price is predicted through a comparison of present and historical yields. To overcome breaches in security, a blockchain technique is employed in this work to secure communication between farmers, investors and merchants. The investor dispatches instructions on the selection of the seed and fertilizer, as well as the crop cost, through the blockchain to the farmer and the merchant. Such secure communication bypasses third-party involvement and inconsistencies in the data. When compared to the traditional method, the proposed technique offers better accuracy and profits, right from seed selection to trading. The proposed IANN technique produced a higher yield than the traditional method with a profit of 51%, 35% and 20% for rice, bananas and flowers, respectively. Similarly, the IANN technique provides 99.15% prediction accuracy in terms of a profit analysis. The blockchain and edge computing-based transactions improve security and reduce transactional latency. The proposed system ensures sustainability and traceability in agriculture.
Internet of Things plays a significant role in multiple sectors like agriculture, manufacturing and healthcare for collecting information to automation. The collected information is in different diversity and consists of confidential and non-confidential information. Secure handling of confidential data is a crucial task in cloud computing like storage, access control and monitoring. The blockchain based storage technique provides immutable data storage, efficient access control and dynamic monitoring to confidential data. Thus, the secure internet of things data storage, access control and monitoring using blockchain technique is proposed in this work. The patients health information that are in different formats are pruned by a decision tree algorithm and it classifies the confidential data and nonconfidential data by the fuzzy rule classification technique. Depending on data owner's willing, the fuzzy rule is framed and the confidential and non-confidential data collected by internet of things sensors are classified. To provide confidentiality to confidential data, Attribute Based Encryption is applied to confidential data and stored in an off-chain mode of blockchain instead of entire data encryption and storage. The non-confidential data is stored in a plaintext form in cloud storage. When compared to support vector machine, K-nearest neighbor and Naive Bayes classification techniques, the proposed fuzzy rule based confidential data identification produces greater than 96 % of accuracy based on data owner willing and confidential data storage takes lesser than 20 % of storage space and processing time in an entire data storage. Additionally, the blockchain performances like throughput, network scalability and latency is optimized through minimal block size and transactions. Thus, our experimental results show that the proposed blockchain based internet of things data storage, access control and monitoring technique provides better confidentiality and access control to confidential data than the conventional cloud storage technique with lesser processing time.
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