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In recent years, both the Internet of Things (IoT) and blockchain technologies have been highly influential and revolutionary. IoT enables companies to embrace Industry 4.0, the Fourth Industrial Revolution, which benefits from communication and connectivity to reduce cost and to increase productivity through sensor-based autonomy. These automated systems can be further refined with smart contracts that are executed within a blockchain, thereby increasing transparency through continuous and indisputable logging. Ideally, the level of security for these IoT devices shall be very high, as they are specifically designed for this autonomous and networked environment. This paper discusses a use case of a company with legacy devices that wants to benefit from the features and functionality of blockchain technology. In particular, the implications of retrofit solutions are analyzed. The use of the BISS:4.0 platform is proposed as the underlying infrastructure. BISS:4.0 is
intended to integrate the blockchain technologies into existing enterprise environments. Furthermore, a security analysis of IoT and blockchain present attacks and countermeasures are presented that are identified and applied to the mentioned use case.
This paper presents an overview of EREMI, a two-year project funded under ERASMUS+ KA203, and its results. The project team’s main objective was to develop and validate an advanced interdisciplinary higher education curriculum, which includes lifelong learning components. The curriculum focuses on enhancing resource efficiency in the manufacturing industry and optimising poorly or non-digitised industrial physical infrastructure systems. The paper also discusses the results of the project, highlighting the successful achievement of its goals. EREMI effectively supports the transition to Industry 5.0 by preparing a common European pool of future experts. Through comprehensive research and collaboration, the project team has designed a curriculum that equips students with the necessary skills and knowledge to thrive in the evolving manufacturing landscape. Furthermore, the paper explores the significance of EREMI’s contributions to the field, emphasising the importance of resource efficiency and system optimisation in industrial settings. By addressing the challenges posed by under-digitised infrastructure, the project aims to drive sustainable and innovative practices in manufacturing. All five project partner organisations have been actively engaged in offering relevant educational content and framework for decentralised sustainable economic development in regional and national contexts through capacity building at a local level. A crucial element of the added value is the new channel for obtaining feedback from students. The survey results, which are outlined in the paper, offer valuable insights gathered from students, contributing to the continuous improvement of the project.
Deep learning approaches are becoming increasingly important for the estimation of the Remaining Useful Life (RUL) of mechanical elements such as bearings. This paper proposes and evaluates a novel transfer learning-based approach for RUL estimations of different bearing types with small datasets and low sampling rates. The approach is based on an intermediate domain that abstracts features of the bearings based on their fault frequencies. The features are processed by convolutional layers. Finally, the RUL estimation is performed using a Long Short-Term Memory (LSTM) network. The transfer learning relies on a fixed-feature extraction. This novel deep learning approach successfully uses data of a low-frequency range, which is a precondition to use low-cost sensors. It is validated against the IEEE PHM 2012 Data Challenge, where it outperforms the winning approach. The results show its suitability for low-frequency sensor data and for efficient and effective transfer learning between different bearing types.
Embedded Analog Physical Unclonable Function System to Extract Reliable and Unique Security Keys
(2020)
Internet of Things (IoT) enabled devices have become more and more pervasive in our everyday lives. Examples include wearables transmitting and processing personal data and smart labels interacting with customers. Due to the sensitive data involved, these devices need to be protected against attackers. In this context, hardware-based security primitives such as Physical Unclonable Functions (PUFs) provide a powerful solution to secure interconnected devices. The main benefit of PUFs, in combination with traditional cryptographic methods, is that security keys are derived from the random intrinsic variations of the underlying core circuit. In this work, we present a holistic analog-based PUF evaluation platform, enabling direct access to a scalable design that can be customized to fit the application requirements in terms of the number of required keys and bit width. The proposed platform covers the full software and hardware implementations and allows for tracing the PUF response generation from the digital level back to the internal analog voltages that are directly involved in the response generation procedure. Our analysis is based on 30 fabricated PUF cores that we evaluated in terms of PUF security metrics and bit errors for various temperatures and biases. With an average reliability of 99.20% and a uniqueness of 48.84%, the proposed system shows values close to ideal.
Hybrid low-voltage physical unclonable function based on inkjet-printed metal-oxide transistors
(2020)
Modern society is striving for digital connectivity that demands information security. As an emerging technology, printed electronics is a key enabler for novel device types with free form factors, customizability, and the potential for large-area fabrication while being seamlessly integrated into our everyday environment. At present, information security is mainly based on software algorithms that use pseudo random numbers. In this regard, hardware-intrinsic security primitives, such as physical unclonable functions, are very promising to provide inherent security features comparable to biometrical data. Device-specific, random intrinsic variations are exploited to generate unique secure identifiers. Here, we introduce a hybrid physical unclonable function, combining silicon and printed electronics technologies, based on metal oxide thin film devices. Our system exploits the inherent randomness of printed materials due to surface roughness, film morphology and the resulting electrical characteristics. The security primitive provides high intrinsic variation, is non-volatile, scalable and exhibits nearly ideal uniqueness.
The integration of Internet of Things devices onto the Blockchain implies an increase in the transactions that occur on the Blockchain, thus increasing the storage requirements.
A solution approach is to leverage cloud resources for storing blocks within the chain. The paper, therefore, proposes two solutions to this problem. The first being an improved hybrid architecture design which uses containerization to create a side chain on a fog node for the devices connected to it and an Advanced Time‑variant Multi‑objective Particle Swarm Optimization Algorithm (AT‑MOPSO) for determining the optimal number of blocks that should be transferred to the cloud for storage. This algorithm uses time‑variant weights for the velocity of the particle swarm optimization and the non‑dominated sorting and mutation schemes from NSGA‑III. The proposed algorithm was compared with results from the original MOPSO algorithm, the Strength Pareto Evolutionary Algorithm (SPEA‑II), and the Pareto Envelope‑based Selection Algorithm with region‑based selection (PESA‑II), and NSGA‑III. The proposed AT‑MOPSO showed better results than the aforementioned MOPSO algorithms in cloud storage cost and query probability optimization. Importantly, AT‑MOPSO achieved 52% energy efficiency compared to NSGA‑III.
To show how this algorithm can be applied to a real‑world Blockchain system, the BISS industrial Blockchain architecture was adapted and modified to show how the AT‑MOPSO can be used with existing Blockchain systems and the benefits it provides.
Blockchain interoperability: the state of heterogenous blockchain-to-blockchain communication
(2023)
Blockchain technology has been increasingly adopted over the past few years since the introduction of Bitcoin, with several blockchain architectures and solutions being proposed. Most proposed solutions have been developed in isolation, without a standard protocol or cryptographic structure to work with. This has led to the problem of interoperability, where solutions running on different blockchain platforms are unable to communicate, limiting the scope of use. With blockchains being adopted in a variety of fields such as the Internet of Things, it is expected that the problem of interoperability if not addressed quickly, will stifle technology advancement. This paper presents the current state of interoperability solutions proposed for heterogenous blockchain systems. A look is taken at interoperability solutions, not only for cryptocurrencies, but also for general data-based use cases. Current open issues in heterogenous blockchain interoperability are presented. Additionally, some possible research directions are presented to enhance and to extend the existing blockchain interoperability solutions. It was discovered that though there are a number of proposed solutions in literature, few have seen real-world implementation. The lack of blockchain-specific standards has slowed the progress of interoperability. It was also realized that most of the proposed solutions are developed targeting cryptocurrency-based applications.
Industrial companies can use blockchain to assist them in resolving their trust and security issues. In this research, we provide a fully distributed blockchain-based architecture for industrial IoT, relying on trust management and reputation to enhance nodes’ trustworthiness. The purpose of this contribution is to introduce our system architecture to show how to secure network access for users with dynamic authorization management. All decisions in the system are made by trustful nodes’ consensus and are fully distributed. The remarkable feature of this system architecture is that the influence of the nodes’ power is lowered depending on their Proof of Work (PoW) and Proof of Stake (PoS), and the nodes’ significance and authority is determined by their behavior in the network.
This impact is based on game theory and an incentive mechanism for reputation between nodes. This system design can be used on legacy machines, which means that security and distributed systems
can be put in place at a low cost on industrial systems. While there are no numerical results yet, this work, based on the open questions regarding the majority problem and the proposed solutions based on a game-theoretic mechanism and a trust management system, points to what and how industrial IoT and existing blockchain frameworks that are focusing only on the power of PoW and PoS can be secured more effectively.
With many advances in sensor technology and the Internet of Things, Vehicle Ad Hoc Net- work (VANET) is becoming a new generation. VANET’s current technical challenges are deploying decentralized architecture and protecting privacy. Because Blockchain features are decentralized, distributed, mass storage, and non-manipulation features, this paper designs a new decentralized architecture using Blockchain technology called Blockchain-based VANET. Blockchain-based VANET can effectively resolve centralized problems and mutual distrust between VANET units. To achieve this, it is needed to provide scalability on the blockchain to run for VANET. In this system, our focus is on the reliability of incoming messages on the network. Vehicles check the validity of the received messages using the proposed Bayesian formula for trust management system and some information saved in the Blockchain. Then, based on the validation result, the vehicle computes a rate for each message type and message source vehicle. Vehicles upload the computed rates to Roadside Units (RSUs) in order to calculate the net reliability value. Finally, RSUs using a sharding consensus mechanism generate blocks, including the net reliability value as a transaction. In this system, all RSUs collaboratively maintain the latest updated Blockchain. Our experimental results show that the proposed system is effective, scalable and dependable in data gathering, computing, organization, and retrieval of trust values in VANET.
The increase of the Internet of Things (IoT) calls for secure solutions for industrial applications. The security of IoT can be potentially improved by blockchain. However, blockchain technology suffers scalability issues which hinders integration with IoT. Solutions to blockchain’s scalability issues, such as minimizing the computational complexity of consensus algorithms or blockchain storage requirements, have received attention. However, to realize the full potential of blockchain in IoT, the inefficiencies of its inter-peer communication must also be addressed. For example, blockchain uses a flooding technique to share blocks, resulting in duplicates and inefficient bandwidth usage. Moreover, blockchain peers use a random neighbor selection (RNS) technique to decide on other peers with whom to exchange blockchain data. As a result, the peer-to-peer (P2P) topology formation limits the effective achievable throughput. This paper provides a survey on the state-of-the-art network structures and communication mechanisms used in blockchain and establishes the need for network-based optimization. Additionally, it discusses the blockchain architecture and its layers categorizes existing literature into the layers and provides a survey on the state-of-the-art optimization frameworks, analyzing their effectiveness and ability to scale. Finally, this paper presents recommendations for future work.