Teegraph: A Blockchain consensus algorithm based on TEE and DAG for data sharing in IoT

Selective blockchain system for secure and efficient D2D communication

In recent years, consensus algorithms have gained significant importance in the context of blockchain networks. These algorithms play a crucial role in allowing network participants to reach agreements on the state of the blockchain without needing a central authority. The present study focuses on carrying out a systematic mapping of these consensus algorithms to explore in detail their use, benefits, and challenges in the context of blockchain networks. Understanding consensus algorithms is essential to appreciating how blockchain networks achieve the reliability and integrity of their distributed ledgers. These algorithms allow network nodes to reach agreement on the validity of transactions and the creation of new blocks on the blockchain. In this sense, consensus algorithms are the engine that drives trust in these decentralized networks. Numerous authors have contributed to the development and understanding of consensus algorithms in the context of blockchain networks. This revolutionary concept paved the way for numerous cryptocurrencies and blockchain systems. Despite advances in this field, significant challenges remain: centralization, fair token distribution, scalability, and sustainability. The energy consumption of blockchain networks, particularly those using algorithms such as Proof of Work, Proof of Stake, Delegated Proof of Stake, Proof of Authority, and hybrid algorithms (Proof of Work/Proof of Stake), has raised concerns about their environmental impact, motivating the scientific and technological community to investigate more sustainable alternatives that promise to reduce energy consumption and contribute to climate change mitigation. Furthermore, interoperability between different blockchains and security in specific environments, such as IoT, are areas that still require significant research attention. This systematic mapping not only seeks to shed light on the current state of consensus algorithms in blockchain, but also their impact on sustainability, identifying those algorithms that, in addition to guaranteeing integrity and security, minimize the environmental footprint, promoting a more efficient use of energy resources, being a relevant approach in a context in which the adoption of sustainable technologies has become a global priority. Understanding and improving these algorithms are critical to unlocking the full potential of blockchain technology in a variety of applications and industry sectors.

Blockchain is a distributed, decentralized ledger mechanism with a various features. It is used in diverse applications nowadays, from financial sector to password management. It does not have any central tool to validate and verify the transactions, yet every transaction in the Blockchain is secured and verified. This is achieved because of a consensus algorithm in the network. Latest study reports show that emergence of quantum computing will impact the overall safety of Blockchain and its internal working. Attacks using Grover's and Shor's algorithm can threaten the hashing and public key schemes in cryptography. It will force a complete redesign of the Blockchain systems to withstand quantum attacks. So there is a need to develop quantum-safe Blockchain systems. Consensus mechanisms like Proof of Work (PoW) and Signing algorithms like Elliptic Curve Cryptography used in Blockchain can be modified to overcome quantum attacks. Here a comparative study and analysis of different consensus algorithms developed using post-quantum cryptosystems are done, which can be implemented in Blockchain systems to make them quantum safe.

The rapid proliferation of Internet of Things (IoT) devices has ushered in a new era of connectivity and data exchange, revolutionizing various industries. However, the inherent vulnerabilities in traditional centralized transaction systems pose significant security challenges, particularly when dealing with sensitive data generated by IoT devices. This paper introduces an ICAA (Integrity Consensus Authorization Algorithm) for securing transaction records over the IoT network by leveraging Decentralized Distributed Ledger Technology (DDL), integrating the PICA (Proof-of-Integrity Consensus Algorithm) and CTAP (Context-Aware Transaction Authorization Protocol). The proposed system addresses the limitations of centralized architectures by employing a decentralized ledger, ensuring transparency, immutability, and tamper-resistant transaction records. The Proof-of-Integrity Consensus Algorithm enhances the security of the network by validating and confirming transactions based on the integrity of the data stored in the distributed ledger. This consensus mechanism minimizes the risk of fraudulent activities and unauthorized modifications, making it well-suited for the dynamic and distributed nature of IoT environments. Furthermore, the integration of the Context-Aware Transaction Authorization Protocol enhances the adaptability of the system to the diverse contexts in which IoT devices operate. The synergy between the Proof-of-Integrity Consensus Algorithm and the Context-Aware Transaction Authorization Protocol creates a comprehensive and secure framework for managing transaction records in IoT networks. . The proposed HGGC is 5.026% better than the ECMQV-MAC, 0.4215% better than QKD, and 0.0843% better than OTP in the nodes 200. The proposed model contributes to the establishment of a trustworthy and resilient infrastructure for the IoT, laying the foundation for secure and transparent transactions in the connected world.

In general, the Internet of Things (IoT) relies on centralized servers due to limited computing power and storage capacity. These server-based architectures have vulnerabilities such as DDoS attacks, single-point errors, and data forgery, and cannot guarantee stability and reliability. Blockchain technology can guarantee reliability and stability with a P2P network-based consensus algorithm and distributed ledger technology. However, it requires the high storage capacity of the existing blockchain and the computational power of the consensus algorithm. Therefore, blockchain nodes for IoT data management are maintained through an external cloud, an edge node. As a result, the vulnerability of the existing centralized structure cannot be guaranteed, and reliability cannot be guaranteed in the process of storing IoT data on the blockchain. In this paper, we propose a multi-level blockchain structure and consensus algorithm to solve the vulnerability. A multi-level blockchain operates on IoT devices, and there is an IoT chain layer that stores sensor data to ensure reliability. In addition, there is a hyperledger fabric-based monitoring chain layer that operates the access control for the metadata and data of the IoT chain to lighten the weight. We propose an export consensus method between the two blockchains, the Schnorr signature method, and a random-based lightweight consensus algorithm within the IoT-Chain. Experiments to measure the blockchain size, propagation time, consensus delay time, and transactions per second (TPS) were conducted using IoT. The blockchain did not exceed a certain size, and the delay time was reduced by 96% to 99% on average compared to the existing consensus algorithm. In the throughput tests, the maximum was 1701 TPS and the minimum was 1024 TPS.

In the burgeoning era of digital finance, ensuring user privacy protection within blockchain systems has become a crucial concern. Despite this, existing privacy enhancement methods often lack user-friendliness, as they necessitate users to navigate complex protocols, thereby raising the barrier to entry. This paper introduces EPT, an efficient framework that not only addresses the user privacy concern but also enhances usability. Our method allows users to interact with confidential smart contracts deployed in a Trusted Execution Environment (TEE) by sending private transactions directly to the blockchain. We devise a secure TEE attestation and data privacy scheme for secure private transactions, even when users interact indirectly with the TEE. Further, we utilize a robust data acquisition approach for inputting valid and fresh private transaction-related data into the TEE. Our extensive evaluations demonstrate that EPT can deliver confidential transactions at a gas cost comparable to that of non-confidential block transactions, with a high throughput of 2, 715 tx/s, and an end-to-end latency of around 12 seconds.

There is an increasing emphasis on securing deep learning (DL) inference pipelines for mobile and IoT applications with privacy-sensitive data. Prior works have shown that privacy-sensitive data can be secured throughout deep learning inferences on cloud-offloaded models through trusted execution environments such as Intel SGX. However, prior solutions do not address the fundamental challenges of securing the resource-intensive inference tasks on low-power, low-memory devices (e.g., mobile and IoT devices), while achieving high performance. To tackle these challenges, we propose SecDeep, a low-power DL inference framework demonstrating that both security and performance of deep learning inference on edge devices are well within our reach. Leveraging TEEs with limited resources, SecDeep guarantees full confidentiality for input and intermediate data, as well as the integrity of the deep learning model and framework. By enabling and securing neural accelerators, SecDeep is the first of its kind to provide trusted and performant DL model inferencing on IoT and mobile devices. We implement and validate SecDeep by interfacing the ARM NN DL framework with ARM TrustZone. Our evaluation shows that we can securely run inference tasks with 16× to 172× faster performance than no acceleration approaches by leveraging edge-available accelerators.

Nowadays, blockchain is emerging as a worthwhile technology for managing sensitive data in electronic healthcare system. It plays an important role in healthcare, medical research and insurance sectors. The consensus algorithms used in blockchain technology for the selection of a new block, provide high-level of security to IoT devices. However, the reliability problem still exists. In the present paper, a blockchain based hybrid consensus mechanism (HCM) is implemented in electronic healthcare system (EHS) to overcome trustworthiness issues. The aim of the proposed HCM is to maintain reputation module on the basis of the block activities. In this context, EHS is designed in four layers namely: system layer, inter-network layer, blockchain layer, and cloud layer. Moreover, HCM consists of five algorithms for creation, validation, fork handling (if any), Merkle tree construction and reward/punishment module respectively. Dev C++ software platform is used for the simulation of the above mentioned HCM algorithms excluding Merkle tree construction which is simulated using conditional contrast high itemset tree. It is observed that all the blocks use same methodology to be the part of a new blockchain network. Moreover, the CPU and memory consumption in the implementation of HCM is always below two percent and about fifty percent respectively as shown in the latency graph. The basic security goal (confidentiality, integrity and availability) is guaranteed with the help of the height of the Merkel tree as well. The performances of the proposed HCM and Proof of X-repute (PoXR) blockchain consensus algorithms are compared with respect to various parameters such as final difficulty, reward and punishment provisions etc. HCM shows superior performance as the final earned reputation is calculated for each block along with the reward and punishment modules during the deployment of blockchain network. In addition, a simple concept of Merkle-tree is opted for providing reward and punishment rather than a set of complex mathematical equations as used in PoXR consensus algorithm.

Blockchain technology is an emerging decentralized and distributed technology that can maintain data security. It has the potential to transform many sectors completely. The core component of blockchain networks is the consensus algorithm because its efficiency, security, and scalability depend on it. A consensus problem is a difficult and significant task that must be considered carefully in a blockchain network. It has several practical applications such as distributed computing, load balancing, and blockchain transaction validation. Even though a lot of consensus algorithms have been proposed, the majority of them require many computational and communication resources. Similarly, they also suffer from high latency and low throughput. In this work, we proposed a new consensus algorithm for consortium blockchain for a leader selection using the reputation value of nodes and the voting process to ensure high performance. A security analysis is conducted to demonstrate the security of the proposed algorithm. The outcomes show that the proposed algorithm provides a strong defense against the network nodes’ abnormal behavior. The performance analysis is performed by using Hyperledger Fabric v2.1 and the results show that it performs better in terms of throughput, latency, CPU utilization, and communications costs than its rivals Trust-Varying Algo, FP-BFT, and Scalable and Trust-based algorithms.

Modern industry 4.0 applications are shifting towards decentralized automation of computing and cyber-physical systems (CPS), which necessitates building a robust, secure, and efficient system that performs complex interactions with other physical processes. To handle complex interactions in CPS, trust and consensus among various stakeholders is a prime concern. In a similar direction, consensus algorithms in blockchain have evolved over the years that focus on building smart, robust, and secure CPS. Thus, it is imperative to understand the key components, functional characteristics, and architecture of different consensus algorithms used in CPS. Many consensus algorithms exist in the literature with a specified set of functionalities, performance, and computing services. Motivated from these facts, in this survey, we present a comprehensive analysis of existing state-of-the-art consensus mechanisms and highlight their strength and weaknesses in decentralized CPS applications. In the first part, we present the scope of the proposed survey and identify gaps in the existing surveys. Secondly, we present the review method and objectives of the proposed survey based on research questions that address the gaps in existing studies. Then, we present a solution taxonomy of decentralized consensus mechanisms for various CPS applications. Then, open issues and challenges are also discussed in deploying various consensus mechanisms in the CPS with their merits and demerits. The proposed survey will act as a road-map for blockchain developers and researchers to evaluate and design future consensus mechanisms, which helps to build an efficient CPS for industry 4.0 stakeholders.

Blockchain technology presents significant security challenges despite its transformative impact on digital transactions and decentralized data management. Key vulnerabilities include insecure smart contract execution, data privacy risks on transparent ledgers, and susceptibility of certain consensus mechanisms to attacks. Trusted Execution Environments (TEEs) offer a robust hardware-based solution to these critical issues. By providing isolated execution spaces, TEEs safeguard code and data confidentiality and integrity, thereby fundamentally strengthening blockchain security. This paper presents a comprehensive analysis of TEEs in blockchain technology. First, we analyze the challenges inherent in blockchain systems and demonstrate the advantages of TEEs over current methods. A detailed analysis of TEE properties, variants, and evolution in the blockchain field is provided. Additionally, we explore innovative TEE-based solutions across three key application domains: consensus mechanism optimization, confidential computation and execution, and payment networks and financial applications. Furthermore, we propose a research agenda addressing current challenges such as vulnerabilities to side-channel attacks and dependencies on hardware trust assumptions. Finally, we propose five critical directions for future TEE-blockchain integration: enhancement of security and privacy protection with particular attention to the Trusted Computing Base (TCB) minimization, performance optimization through hardware architecture advancement, trust model refinement to reduce centralization, expansion of application scenarios through interdisciplinary collaboration, and development of cross-chain interoperability standards. Our work contributes to blockchain security knowledge and provides a roadmap for researchers and practitioners in this rapidly evolving field.

Ensuring privacy of online messaging remains a challenge. While the contents or data of online communications are often protected by end-to-end encryption, the metadata of communications are not. Metadata such as who is communicating with whom, how much, and how often, are leaked by popular messaging systems today. In the last four decades we have witnessed a rich literature of designs towards metadata-protecting communications systems (MPCS). While recent MPCS works often target metadata-protected messaging systems, no existing construction simultaneously attains four desirable properties for messaging systems, namely (i) low latency, (ii) high throughput, (iii) horizontal scalability, and (iv) asynchronicity. Existing designs often capture disjoint subsets of these properties. For example, PIR-based approaches achieve low latency and asynchronicity but have low throughput and lack horizontal scalability, mixnet-based approaches achieve high throughput and horizontal scalability but lack asynchronicity, and approaches based on trusted execution environments (TEEs) achieve high throughput and asynchronicity but lack horizontal scalability. In this work, we present TEEMS, the first MPCS designed for metadata-protected messaging that simultaneously achieves all four desirable properties. Our distributed TEE-based system uses an oblivious mailbox design to provide metadata-protected messaging. TEEMS presents novel oblivious routing protocols that adapt prior work on oblivious distributed sorting. Moreover, we introduce the notion of ID and token channels to circumvent shortcomings of prior designs. We empirically demonstrate TEEMS' ability to support 2^20 clients engaged in metadata-protected conversations in under 1 s, with 205 cores, achieving an 18× improvement over prior work for latency and throughput, while supporting significantly better scalability and asynchronicity properties.

To implement a blockchain, the trend is now to integrate a non-trivial Byzantine fault-tolerant consensus algorithm instead of the seminal idea of waiting to receive blocks to decide upon the longest branch. After a dozen years of existence, blockchains trade now large amounts of valuable assets and a simple disagreement could lead to disastrous losses. Unfortunately, Byzantine consensus solutions used in blockchains are at best proved correct “by hand” as we are not aware of any of them having been automatically verified. We propose two contributions: (i) we illustrate the severity of the problem by listing six vulnerabilities of blockchain consensus including two new counter-examples; (ii) we then formally verify two Byzantine fault-tolerant components of Red Belly Blockchain (Crain et al. in Red belly: a secure, fair and scalable open blockchain, 2021, [32]) using the ByMC model checker. First, we specify its simple broadcast primitive in 116 lines of code that is verified in 40 s on a 2-core Intel machine. Then, we specify its blockchain consensus algorithm in 276 lines of code and assume a round-rigid adversary to verify in 17 minutes on a 64-core AMD machine using MPI. To conclude, we argue that it has now become both possible and crucial to formally verify the correctness of blockchain consensus protocols.

Cyber security in the banking sector is of high importance nowadays. The rate of cyberattacks is spiking every year, and the implementation of strong cybersecurity models is required to ensure the confidentiality and integrity of data. Since protecting a bank requires a wide range of security practices, this paper focuses on protecting the bank resources from malicious actors and securing the transactions using a blockchain consensus mechanism that uses a zero‐trust security approach among the participants in the transaction. In addition to the framework, an algorithm for blockchain‐based online transactions was designed to make use of practical implementation in the future. The ideas formulated during the research and literature review were integrated to design the framework and the algorithm. The proposed framework ensures that the security of the banking sector can be enhanced by adopting the zero‐trust concept and blockchain technology. The consensus algorithms used for the transaction make it immutable and decentralized. Zero‐trust principles adopted in the model ensure the confidentiality and integrity of the banking system.

As a distributed shared ledger and database technology, blockchain has the characteristics of decentralization, tamper-proof, openness and transparency. With the continuous development of blockchain technology, the technology has received high attention from government departments, finance, technology and other industries. The key technology of blockchain is the design of consensus algorithm, which affects the overall efficiency and performance of the blockchain system. How to achieve consistency and efficiency among nodes in a simple and efficient blockchain distributed system. This paper divides consensus algorithms into CFT and BFT according to fault tolerance types, and analyzes the basic principles and consensus process of each algorithm in detail. In five aspects of block generation speed, degree of decentralization, security, consistency and resource consumption, the mainstream consensus algorithms in the blockchain are compared and analyzed, the advantages and disadvantages of each consensus algorithm are summarized. Finally, the future blockchain consensus algorithms are summarized and prospected.