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Blockchain Platforms for IoT Use-cases
Abstract
This is an extended abstract to be presented at the 2nd Symposium on Distributed Ledger Technology - SDLT'2018 at Griffith University. In this research, we have briefly explored the feasibility of three major public blockchain systems suitable for IoT use-cases against a set of chosen criteria.
... The popularity of BC lies in its multiple properties that enable it to be an effective mechanism to address the issues involving IIoT, as already applied in IoT [19]. ...
... Scalability [6,19]: The selected architectures must be able to withstand the significant amount of generated traffic. Most of the centralized cloud-based architectures cannot efficiently cope with that. ...
... Privacy [2,6,19,23]: By default, all IIoT devices are identified either by their public key or their hash. As a result, their anonymity is not guaranteed in case this is required. ...
This paper aims at identifying the main challenges associated with the adoption of blockchain and smart contract technologies as potential solutions for cybersecurity in an Industrial Internet of Things environment. Initially, an introduction to IIoT, blockchain and smart contracts is made, highlighting their core concepts as well as explaining their characteristics and properties. Subsequently, based on a literature review, the various benefits and challenges for their implementation are identified. The latter are presented through a hierarchical approach that first categorizes them in architecture and privacy related challenges, with each category being further divided into more specific challenges to emphasize the complex nature of the problem. Some typical use cases are also mentioned to showcase the feasibility of these technologies. Finally, a conceptual framework for IIoT cybersecurity is proposed in terms of future work directions.KeywordsIndustrial Internet of Things (IIoT)Smart ManufacturingBlockchainSmart ContractsCybersecurity
... Recently, blockchain technology has been involved in various application areas beyond the cryptocurrency domain since it has multiple features, such as decentralisation, support for integrity, resiliency, autonomous control, and anonymity [57]. Blockchain eliminates a central authority by using a distributed ledger and is decentralised to provide more efficiency for operating and controlling communication among all participating nodes. ...
Rapid development in science and information technologies, such as the Internet of things, has led to a growth in the number of studies and research papers on smart cities in recent years and more specifically on the construction of smart campus technologies. This paper will review the concept of a smart campus, discuss the main technologies deployed, and then propose a new novel framework for a smart campus. The architecture of this new smart campus approach will be discussed with particular consideration of security and privacy systems, the Internet of things, and blockchain technologies.
... Recently, blockchain technology has been involved in various application areas beyond the cryptocurrency domain since it has multiple features, such as decentralisation, support for integrity, resiliency, autonomous control, and anonymity [57]. Blockchain eliminates a central authority by using a distributed ledger and is decentralised to provide more efficiency for operating and controlling communication among all participating nodes. ...
With the development of technology, e-commerce became an essential part of an individual’s life, where individuals could easily purchase and sell products over the internet. However, fraud attempts; specifically credit card fraudulent attacks are rapidly increasing. Cards may potentially be stolen; fake records are being used and credit cards are subject to being hacked. Artificial Intelligence techniques tackle these credit card fraud attacks, by identifying patterns that predict false transactions. Both Machine Learning and Deep Learning models are used to detect and prevent fraud attacks. Machine Learning techniques provide positive results only when the dataset is small and do not have complex patterns. In contrast, Deep Learning deals with huge and complex datasets. However, most of the existing studies on Deep Learning have used private datasets, and therefore, did not provide a broad comparative study. This paper aims to improve the detection of credit card fraud attacks using Long Short-Term Memory Recurrent Neural Network (LSTM RNN) with a public dataset. Our proposed model proved to be effective. It achieved an accuracy rate of 99.4% which is higher compared to other existing Machine and Deep Learning techniques.
... Any erroneous event or actions/decision can be identi ed at the source and immediate corrective actions could be taken to reduce the impacts. Towards this aim, several researchers have explored the suitability of integrating IoT and blockchain in di erent applications domains [12,13,14,15,16,17,18,19]. ...
The Internet of Things (IoT) is experiencing an exponential growth in a wide variety of use-cases in multiple application domains, such as healthcare, agriculture, smart cities, smart homes, supply chain, and so on. To harness its full potential, it must be based upon a resilient network architecture with strong support for security, privacy, and trust. Most of these issues still remain to be addressed carefully for the IoT systems. Blockchain technology has recently emerged as a breakthrough technology with the potential to deliver some valuable properties such as resiliency, support for integrity, anonymity,
decentralization, and autonomous control. A number of blockchain platforms are proposed that may be suitable for different use-cases including IoT applications. In such, the possibility to integrate the IoT and blockchain technology is seen as a potential solution to address some crucial issues. However, to achieve this, there must be a clear understanding of the requirements of different IoT applications and the suitability of a blockchain platform for a particular application satisfying its underlying requirements. This chapter aims to achieve this goal by describing an evaluation framework which can be utilized to select a suitable blockchain platform for a given IoT application.
Rapid development in advanced technologies such as the Internet of Things (IoT) and Blockchain has led to a growth of interest in a number of application areas, including smart environments such as a smart campus, which can be considered as an example of a smart city. Despite such growth, no comprehensive guiding framework has been developed for emerging IoT and Blockchain technologies deployment in the smart campus environment, particularly in relation to security and privacy aspects, as well as to the mitigation of known problems with IoT and Blockchain in existing applications. This chapter proposes a novel architecture framework for the IoT and Blockchain applications deployed within a smart campus environment, comparing the main technologies involved. As a specific example, this framework is tested for integration of Blockchain and other relevant technologies into the higher education certificating system for issuing authentic, verifiable and sharable student credentials. The existing certificating systems are marked by their lack of speed and low reliability and, in certain educational systems, they produce social and cultural conflicts. The proposed Blockchain-based student certification system is aimed to address these existing problems. Specific higher education institutes in Saudi Arabia were used as a case study to present a certificate validation and sharing framework that guarantees authenticity through leveraging the privacy and security features of a Blockchain network. The proposed solution was validated with the user acceptance study. Two groups of participants, employers and academic users, with a majority of female respondents, were included in this empirical study focusing on the evaluation of the proposed framework, assessing the potential for Blockchain adoption in higher education. The validity and reliability of the framework was tested using a sequential mixed methods design involving the collection of qualitative interview data and quantitative survey data. The results of this study are particularly useful in the context of developing countries. It is expected that the proposed framework will have useful applications in a variety of fields, where it is necessary to determine whether a satisfactory level of IoT and Blockchain technologies has been achieved and maintained in accordance with the relevant safety and security standards.KeywordsSmart campusInternet of ThingsBlockchainSecurityPrivacyTrustSmart HE certificate
The Internet of Things (IoT) has recently emerged as an innovative technology capable of empowering various areas such as healthcare, agriculture, smart cities, smart homes and supply chain with real-time and state-of-the-art sensing capabilities. Due to the underlying potential of this technology, it already saw exponential growth in a wide variety of use-cases in multiple application domains. As researchers around the globe continue to investigate its aptitudes, a collective agreement is that to get the best out of this technology and to harness its full potential, IoT needs to sit upon a flexible network architecture with strong support for security, privacy and trust. On the other hand, blockchain (BC) technology has recently come into prominence as a breakthrough technology with the potential to deliver some valuable properties such as resiliency, support for integrity, anonymity, decentralization and autonomous control. Several BC platforms are proposed that may be suitable for different use-cases, including IoT applications. In such, the possibility to integrate the IoT and BC technology is seen as a potential solution to address some crucial issues. However, to achieve this, there must be a clear understanding of the requirements of different IoT applications and the suitability of a BC platform for a particular application satisfying its underlying requirements. This paper aims to achieve this goal by describing an evaluation framework which can be utilized to select a suitable BC platform for a given IoT application.
In this paper we extend the notion of interactive proofs of assertions to interactive proofs of knowledge. This leads to the
definition of unrestricted input zero-knowledge proofs of knowledge in which the prover demonstrates possession of knowledge
without revealing any computational information whatsoever (not even the one bit revealed in zero-knowledge proofs of assertions).
We show the relevance of these notions to identification schemes, in which parties prove their identity by demonstrating their
knowledge rather than by proving the validity of assertions. We describe a novel scheme which is provably secure if factoring
is difficult and whose practical implementations are about two orders of magnitude faster than RSA-based identification schemes.
The advantages of thinking in terms of proofs of knowledge rather than proofs of assertions are demonstrated in two efficient
variants of the scheme: unrestricted input zero-knowledge proofs of knowledge are used in the construction of a scheme which
needs no directory; a version of the scheme based on parallel interactive proofs (which are not known to be zero knowledge)
is proved secure by observing that the identification protocols are proofs of knowledge.