With the advent of smart homes, smart cities, and smart everything, the Internet of Things (IoT) has emerged as an area of incredible impact, potential, and growth, with Cisco Inc. predicting to have ...50 billion connected devices by 2020. However, most of these IoT devices are easy to hack and compromise. Typically, these IoT devices are limited in compute, storage, and network capacity, and therefore they are more vulnerable to attacks than other endpoint devices such as smartphones, tablets, or computers.
In this paper, we present and survey major security issues for IoT. We review and categorize popular security issues with regard to the IoT layered architecture, in addition to protocols used for networking, communication, and management. We outline security requirements for IoT along with the existing attacks, threats, and state-of-the-art solutions. Furthermore, we tabulate and map IoT security problems against existing solutions found in the literature. More importantly, we discuss, how blockchain, which is the underlying technology for bitcoin, can be a key enabler to solve many IoT security problems. The paper also identifies open research problems and challenges for IoT security.
•IoT is a promising disruptive technology with incredible growth, impact and potential.•A review of emerging topics related to Internet of Things (IoT) security and Blockchain is presented.•A mapping of the major security issues for IoT to possible solutions is tabulated.•Blockchain technology and its robust solutions for challenging and critical IoT security problems are reviewed.•A parametric analysis of the state-of-the-art IoT security issues and solutions is described.
The globalized production and the distribution of agriculture production bring a renewed focus on the safety, quality, and the validation of several important criteria in agriculture and food supply ...chains. The growing number of issues related to food safety and contamination risks has established an immense need for effective traceability solution that acts as an essential quality management tool ensuring adequate safety of products in the agricultural supply chain. Blockchain is a disruptive technology that can provide an innovative solution for product traceability in agriculture and food supply chains. Today's agricultural supply chains are complex ecosystem involving several stakeholders making it cumbersome to validate several important criteria such as country of origin, stages in crop development, conformance to quality standards, and monitor yields. In this paper, we propose an approach that leverages the Ethereum blockchain and smart contracts efficiently perform business transactions for soybean tracking and traceability across the agricultural supply chain. Our proposed solution eliminates the need for a trusted centralized authority, intermediaries and provides transactions records, enhancing efficiency and safety with high integrity, reliability, and security. The proposed solution focuses on the utilization of smart contracts to govern and control all interactions and transactions among all the participants involved within the supply chain ecosystem. All transactions are recorded and stored in the blockchain's immutable ledger with links to a decentralized file system (IPFS) and thus providing to all a high level of transparency and traceability into the supply chain ecosystem in a secure, trusted, reliable, and efficient manner.
Internet of Things (IoT) and blockchain technologies are being heavily exploited and used in may domains, especially for e-healthcare. In healthcare, IoT devices have the ability to provide real-time ...sensory data from patients to be processed and analyzed. Collected IoT data are subjected to centralized computation, processing, and storage. Such centralization can be problematic, as it can be a single point of failure, mistrust, data manipulation and tampering, and privacy evasion. Blockchain can solve such serious problems by providing decentralized computation and storage for IoT data. Therefore, the integration IoT and blockchain technologies can become a reasonable choice for the design of a decentralized IoT-based e-healthcare systems. In this article, first, we give a brief background on blockchain. Second, popular consensus algorithms used in blockchain are discussed in the context of e-health. Third, blockchain platforms are reviewed for their appropriateness in IoT-based e-healthcare. Finally, few use cases are methodologically given to show how key features of the IoT and blockchain can be leveraged to support healthcare services and ecosystems. We also propose a data-flow architecture that combines the IoT with blockchain, called IoBHealth , that can be used for storing, accessing, and managing of e-healthcare data.
Recently, artificial intelligence (AI) and blockchain have become two of the most trending and disruptive technologies. Blockchain technology has the ability to automate payment in cryptocurrency and ...to provide access to a shared ledger of data, transactions, and logs in a decentralized, secure, and trusted manner. Also with smart contracts, blockchain has the ability to govern interactions among participants with no intermediary or a trusted third party. AI, on the other hand, offers intelligence and decision-making capabilities for machines similar to humans. In this paper, we present a detailed survey on blockchain applications for AI. We review the literature, tabulate, and summarize the emerging blockchain applications, platforms, and protocols specifically targeting AI area. We also identify and discuss open research challenges of utilizing blockchain technologies for AI.
With the rise of artificial intelligence (AI) and deep learning techniques, fake digital contents have proliferated in recent years. Fake footage, images, audios, and videos (known as deepfakes) can ...be a scary and dangerous phenomenon and can have the potential of altering the truth and eroding trust by giving false reality. Proof of authenticity (PoA) of digital media is critical to help eradicate the epidemic of forged content. Current solutions lack the ability to provide history tracking and provenance of digital media. In this paper, we provide a solution and a general framework using Ethereum smart contracts to trace and track the provenance and history of digital content to its original source even if the digital content is copied multiple times. The smart contract utilizes the hashes of the interplanetary file system (IPFS) used to store digital content and its metadata. Our solution focuses on video content, but the solution framework provided in this paper is generic enough and can be applied to any other form of digital content. Our solution relies on the principle that if the content can be credibly traced to a trusted or reputable source, the content can then be real and authentic. The full code of the smart contract has been made publicly available at Github.
The advent of blockchain technology can refine the concept of DTs by ensuring transparency, decentralized data storage, data immutability, and peer-to-peer communication in industrial sectors. A DT ...is an integrated multiphysics, multiscale, and probabilistic simulation, representation, and mirroring of a real-world physical component. The DTs help to visualize designs in 3D, perform tests and simulations virtually prior to creation of any physical component, and consequently play a vital role in sustaining and maintaining Industry 4.0. It is anticipated that DTs will become prevalent in the foreseeable future because they can be used for configuration, monitoring, diagnostics, and prognostics. This article envisages how blockchain can reshape and transform DTs to bring about secure manufacturing that guarantees traceability, compliance, authenticity, quality, and safety. We discuss several benefits of employing blockchain in DTs. We taxonomize the DTs literature based on key parameters (e.g., DTs levels, design phases, industrial use cases, key objectives, enabling technologies, and core applications). We provide insights into ongoing progress made towards DTs by presenting recent synergies and case studies. Finally, we discuss open challenges that serve as future research directions.
Big data production in industrial Internet of Things (IIoT) is evident due to the massive deployment of sensors and Internet of Things (IoT) devices. However, big data processing is challenging due ...to limited computational, networking and storage resources at IoT device-end. Big data analytics (BDA) is expected to provide operational- and customer-level intelligence in IIoT systems. Although numerous studies on IIoT and BDA exist, only a few studies have explored the convergence of the two paradigms. In this study, we investigate the recent BDA technologies, algorithms and techniques that can lead to the development of intelligent IIoT systems. We devise a taxonomy by classifying and categorising the literature on the basis of important parameters (e.g. data sources, analytics tools, analytics techniques, requirements, industrial analytics applications and analytics types). We present the frameworks and case studies of the various enterprises that have benefited from BDA. We also enumerate the considerable opportunities introduced by BDA in IIoT. We identify and discuss the indispensable challenges that remain to be addressed, serving as future research directions.
•We investigate the state-of-the-art research studies conducted on IIoT in terms of BDA.•We build a case of BDA for IIoT systems, and classify the literature by devising a taxonomy.•We present frameworks and case studies where BDA processes were used in IIoT systems.•We present several research opportunities, challenges, and future technologies.
There is an immense need of a proof of delivery (PoD) of today's digital media and content, especially those that are subject to payment. Current PoD systems are mostly centralized and heavily ...dependent on a trusted third party (TTP) especially for payment. Such existing PoD systems often lack security, transparency, and visibility, and are not highly credible, as the TTP can be subject to failure, manipulation, corruption, compromise, and hacking. In this paper, we propose a decentralized PoD solution for PoD of digital assets. Our solution leverages key features of blockchain and Ethereum smart contracts to provide immutable and tamper-proof logs, accountability, and traceability. Ethereum smart contracts are used to orchestrate and govern all interactions and transactions including automatic payments in Ether cryptocurrency between customers, digital-content provider, and the file server hosting the digital content. All entities are incentivized to act honestly, and our solution has a mechanism to handle dispute if arisen among participants. The solution has an off-chain secure download phase involving the file server and customers. Moreover, our solution leverages the benefits of interplanetary file system to store the agreed upon terms and conditions between the smart contract actors. A security analysis of our proposed system has been provided. The full code of the smart contract has been publicly made available on Github.
The essence of blockchain smart contracts lies in the execution of business logic code in a decentralized architecture in which the execution outcomes are trusted and agreed upon by all the executing ...nodes. Despite the decentralized and trustless architectures of the blockchain systems, smart contracts on their own cannot access data from the external world. Instead, smart contracts interact with off-chain external data sources, called oracles, whose primary job is to collect and provide data feeds and input to smart contracts. However, there is always risk of oracles providing corrupt, malicious, or inaccurate data. In this paper, we analyze and present the notion of trust in the oracles used in blockchain ecosystems. We analyze and compare trust-enabling features of the leading blockchain oracle approaches, techniques, and platforms. Moreover, we discuss open research challenges that should be addressed to ensure secure and trustworthy blockchain oracles.
This paper formulates the problem of building a
context-aware predictive model
based on user diverse behavioral activities with smartphones. In the area of machine learning and data science, a ...tree-like model as that of decision tree is considered as one of the most popular classification techniques, which can be used to build a data-driven predictive model. The traditional decision tree model typically creates a number of leaf nodes as decision nodes that represent context-specific rigid decisions, and consequently may cause
overfitting
problem in behavior modeling. However, in many practical scenarios within the context-aware environment, the
generalized
outcomes could play an important role to effectively capture user behavior. In this paper, we propose a
behavioral decision tree
, “BehavDT” context-aware model that takes into account user
behavior-oriented generalization
according to individual preference level. The BehavDT model outputs not only the generalized decisions but also the context-specific decisions in relevant exceptional cases. The effectiveness of our BehavDT model is studied by conducting experiments on individual user real smartphone datasets. Our experimental results show that the proposed BehavDT context-aware model is more effective when compared with the traditional machine learning approaches, in predicting user diverse behaviors considering multi-dimensional contexts.
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