Distributed ledgers and blockchain technologies can improve system security and trustworthiness by providing immutable replicated histories of data. Blockchain is a linked list of blocks containing digitally signed transactions, a cryptographic hash of the previous block, and a timestamp stored in a decentralized and distributed network. The Internet of Things (IoT) is one of the application domains in which security based on blockchain is discussed. In this article, we review the structure and architectures of distributed IoT systems and explain the motivations, challenges, and needs of blockchain to secure such systems. However, there are substantial threats and attacks to blockchain that must be understood, as well as suitable approaches to mitigate them. We, therefore, survey the most common attacks to blockchain systems and the solutions to mitigate them, with the objective of assessing how malicious these attacks are in the IoT context.

Blockchain technology has enabled the keeping of a decentralized, tamper-proof, immutable, and ordered ledger of transactional events. Efforts to leverage such a ledger may be challenging when data storage requirements exceed most blockchain protocols’ current capacities. Storing large amounts of decentralized data while maintaining system efficiency is the challenge that we target. This paper proposes using the IPFS distributed hash table (DHT) technology to store information immutably and in a decentralized manner to mitigate the high cost of storage. A storage system involving blockchain and other storage systems in concert should be based on immutable data and allow removal of data from malicious users in the DHT. Efficiency is improved by decreasing the overall processing time in the blockchain with the help of DHT technology and introducing an agreement service that communicate with the blockchain via a RESTful API. We demonstrate the applicability of the proposed method and conclude that the combination of IPFS and blockchain provides efficient cryptographic storage, immutable history and overall better efficiency in a decentralized manner.

Video conferencing applications help people communicate via the Internet and provide a significant and consistent basis for virtual meetings. However, integrity, security, identification, and authentication problems are still universal. Current video conference technologies typically rely on cloud systems to provide a stable and secure basis for executing tasks and processes. At the same time, video conferencing applications are being migrated from centralized to decentralized solutions for better performance without the need for third-party interactions. This article demonstrates a decentralized smart identification scheme for video conferencing applications based on biometric technology, machine learning, and a decentralized hash table combined with blockchain technology. We store users' information on a distributed hash table and transactional events on the distributed ledger after identifying users by implementing machine learning functions. Furthermore, we leverage distributed ledger technology's immutability and traceability properties and distributed hash table unlimited storage feature to improve the system's storage capacity and immutability by evaluating three possible architectures. The experimental results show that an architecture based on blockchain and distributed hash table has better efficiency but needs a longer time to execute than the two other architectures using a centralized database.

Decentralization is essential when trust and performance must not depend on a single organization. Distributed Ledger Technologies (DLTs) and Decentralized Hash Tables (DHTs) are examples where the DLT is useful for transactional events, and the DHT is useful for large-scale data storage. The combination of these two technologies can meet many challenges. The blockchain is a DLT with immutable history protected by cryptographic signatures in data blocks. Identification is an essential issue traditionally provided by centralized trust anchors. Self-sovereign identities (SSIs) are proposed decentralized models where users can control and manage their identities with the help of DHT. However, slowness is a challenge among decentralized identification systems because of many connections and requests among participants. In this article, we focus on decentralized identification by DLT and DHT, where users can control their information and store biometrics. We survey some existing alternatives and address the performance challenge by comparing different decentralized identification technologies based on execution time and throughput. We show that the DHT and machine learning model (BioIPFS) performs better than other solutions such as uPort, ShoCard, and BBID.

User identification in decentralized systems is a demanding task. Identification systems should work resiliently and have efficient performance. Moreover, identification systems should protect the data that they must store against hackers and saboteurs. Keeping a system with decentralized identification without any intervention in the middle has attracted attention to improve earlier centralized identification systems. Decentralized Identifiers (DIDs) constitute a solution for identification divided into different modules. The verifiable data registry is one of the main parts of this technology, which is distributed storage of identity properties. We analyze the decentralized identification data registry and compare the performance of verifiable data registry based on blockchain and the Distributed Hash Table (DHT) on different scales of systems. Our evaluation results show that DHT has better performance. Furthermore, a model based on DHT shows that in addition to immutable storage and faster query time, it makes systems handle or search in data storage with lower searching time compared to Ethereum Blockchain as another immutable secure technology. Finally, our results show that DHT is a better solution than other models in different scenarios. Although blockchain has promising results on a small scale, it still has problems with storage and query time in large-scale systems.

Decentralized identification is an interesting topic for Internet-based systems. Although the use of centralized systems for identification is prevalent, there is still a need for decentralized identification systems that do not rely on a centralized entity. We propose using Distributed Ledger Technology (DLT) to fulfill the needs. Although DLT and Distributed Hash Table (DHT) can be used as technologies in Decentralized Identifiers (DIDs), immutability and the growth of transactions are still challenging. This paper investigates DIDs under the W3C standard and DLT-based technology as one of the solutions for verifiable data registries in DIDs. We evaluate our proposed solution by comparing three models wrt. query time for verifiable data registries. Our proposed architecture for data registry achieves better query time by concealing old transactions from the main DLT.