A blockchain-based deep-learning-driven architecture for quality routing in wireless sensor networks

Over the past few years, great importance has been given to wireless sensor networks (WSNs) as they play a significant role in facilitating the world with daily life services like healthcare, military, social products, etc. However, heterogeneous nature of WSNs makes them prone to various attacks, which results in low throughput, and high network delay and high energy consumption. In the WSNs, routing is performed using different routing protocols like low-energy adaptive clustering hierarchy (LEACH), heterogeneous gateway-based energy-aware multi-hop routing (HMGEAR), etc. In such protocols, some nodes in the network may perform malicious activities. Therefore, four deep learning (DL) techniques and a real-time message content validation (RMCV) scheme based on blockchain are used in the proposed network for the detection of malicious nodes (MNs). Moreover, to analyse the routing data in the WSN, DL models are trained on a state-of-the-art dataset generated from LEACH, known as WSN-DS 2016. The WSN contains three types of nodes: sensor nodes, cluster heads (CHs) and the base station (BS). The CHs after aggregating the data received from the sensor nodes, send it towards the BS. Furthermore, to overcome the single point of failure issue, a decentralized blockchain is deployed on CHs and BS. Additionally, MNs are removed from the network using RMCV and DL techniques. Moreover, legitimate nodes (LNs) are registered in the blockchain network using proof-of-authority consensus protocol. The protocol outperforms proof-of-work in terms of computational cost. Later, routing is performed between the LNs using different routing protocols and the results are compared with original LEACH and HMGEAR protocols. The results show that the accuracy of GRU is 97%, LSTM is 96%, CNN is 92% and ANN is 90%. Throughput, delay and the death of the first node are computed for LEACH, LEACH with DL, LEACH with RMCV, HMGEAR, HMGEAR with DL and HMGEAR with RMCV. Moreover, Oyente is used to perform the formal security analysis of the designed smart contract. The analysis shows that blockchain network is resilient against vulnerabilities. © 2013 IEEE

Exploring Blockchain Data Analysis and Its Communications Architecture: Achievements, Challenges, and Future Directions: A Review Article

Blockchain technology is relatively young but has the potential to disrupt several industries. Since the emergence of Bitcoin, also known as Blockchain 1.0, there has been significant interest in this technology. The introduction of Ethereum, or Blockchain 2.0, has expanded the types of data that can be stored on blockchain networks. The increasing popularity of blockchain technology has given rise to new challenges, such as user privacy and illicit financial activities, but has also facilitated technical advancements. Blockchain technology utilizes cryptographic hashes of user input to record transactions. The public availability of blockchain data presents a unique opportunity for academics to analyze it and gain a better understanding of the challenges in blockchain communications. Researchers have never had access to such an opportunity before. Therefore, it is crucial to highlight the research problems, accomplishments, and potential trends and challenges in blockchain network data analysis and communications. This article aims to examine and summarize the field of blockchain data analysis and communications. The review encompasses the fundamental data types, analytical techniques, architecture, and operations related to blockchain networks. Seven research challenges are addressed: entity recognition, privacy, risk analysis, network visualization, network structure, market impact, and transaction pattern recognition. The latter half of this section discusses future research directions, opportunities, and challenges based on previous research limitations

Security Threats Classification in Blockchains

Blockchain, the foundation of Bitcoin, has become one of the most popular technologies to create and manage digital transactions recently. It serves as an immutable ledger which allows transactions take place in a decentralized manner. This expeditiously evolving technology has the potential to lead to a shift in thinking about digital transactions in multiple sectors including, Internet of Things, healthcare, energy, supply chain, manufacturing, cybersecurity and principally financial services. However, this emerging technology is still in its infancy. Despite the huge opportunities blockchain offers, it suffers from challenges and limitation such as scalability, security, and privacy, compliance, and governance issues that have not yet been thoroughly explored and addressed. Although there are some studies on the security and privacy issues of the blockchain, they lack a systematic examination of the security of blockchain systems. This research conducted a systematic survey of the security threats to the blockchain systems and reviewed the existing vulnerabilities in the Blockchain. These vulnerabilities lead to the execution of the various security threats to the normal functionality of the Blockchain platforms. Moreover, the study provides a case-study for each attack by examining the popular blockchain systems and also reviews possible countermeasures which could be used in the development of various blockchain systems. Furthermore, this study developed taxonomies that classified the security threats and attacks based on the blockchain abstract layers, blockchain primary processes and primary business users. This would assist the developers and businesses to be attentive to the existing threats in different areas of the blockchain-based platforms and plan accordingly to mitigate risk. Finally, summarized the critical open challenges, and suggest future research directions