Blockchain has been used extensively for financial purposes, but this technology can also be beneficial in other contexts where multi-party cooperation, security and decentralization of the data is essential. Properties such as immutability, accessibility and non-repudiation and the existence of smart-contracts make blockchain technology very interesting in robotic contexts that require event registration or integration with Artificial Intelligence. In this paper, we propose a system that leverages blockchain as a ledger to register events and information to be processed by Oracles and uses smart-contracts to control robots by adjusting their velocity, or stopping them, if a person enters the robot working space without permission. We show how blockchain can be used in computer vision problems by interacting with multiple external parties, Oracles, that perform image analysis and how it is possible to use multiple smart-contracts for different tasks. The method proposed is shown in a scenario representing a factory environment, but since it is modular, it can be easily adapted and extended for other contexts, allowing for simple integration and maintenance.
Multimedia data, especially images are increasing dramatically. Images published on the Web are more often facing the risk of being tampered or manipulated since their content is easily mutable. Using blockchain technology provides advantages and, at the same time, challenges when dealing with this issue due to the following reasons: (a) data in a blockchain are well saved and immutable and (b) adding the data directly to a blockchain may consume much time which makes it computationally and economically expensive. Thus, we propose a blockchain-based solution which considers two key aspects: First, using a blockchain to register information about ownership and copyrights for authors, as well as descriptive information of an image, used to detect copyright violations. Second, avoiding insertion of raw image data into the blockchain, but storing only unique descriptive metadata about the images, allowing for a more efficient implementation of the system. This work considers different well-known image matching approaches to validate the power of the proposed approach, which allows for an efficient checking of violations of copyrights for a given image.
Advanced Image and Video Retrieval Techniques
Advanced Steganography and Watermarking Techniques
Rishabh Mehta, Naman Kapoor, Soumya Sourav, Rajeev Shorey
In this paper, we aim to address the major problem of correct image attribution for photos being uploaded on the stock photo websites and peer-to-peer image sharing marketplaces, ensuring that original photographers are rightfully recognized and credited for their works. There are now millions of royalty-free images being shared every week on stock photo websites. There is a major discontent among photographers and graphics designers who share images on such websites regarding a widespread malpractice where others try to take credit for and benefit from original author's work. This happens when someone other than the original author uploads the same image as one already shared on the marketplace or uses image processing methods such as rotation, cropping, gray scale conversion etc and then uploads this tampered image to avoid copyright violation detection. To counter such problems, we propose a decentralised peer-to-peer photo sharing marketplace built on top of Ethereum test chain and demonstrate how it is fair, trustworthy and practical. Our decentralised application leverages perceptual hashes and robust smart contracts of Ethereum to automatically detect and reject tampered images that are perceptually similar to images already present on the marketplace. Due to inherent properties of Blockchain, our marketplace has no central authority controlling it, no third party interference, no single point of failure, zero-censorship and preserves online user privacy. To the best of our knowledge, this is the first work that provides a practical solution for automatically detecting and rejecting perceptually similar images on a decentralised image sharing platform, thus protecting the copyrights of genuine image authors.
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Do Gyun Kim, Jin‐Young Choi, Kiyoung Kim, Jintae Oh
Recently, blockchain technology has been recognized as one of the most important issues for the 4th Industrial Revolution which can be represented by Artificial Intelligence and Internet of Things. Cryptocurrency, named Bitcoin, was the first successful implementation of blockchain, and it triggered the emergence of various cryptocurrencies. In addition, blockchain technology has been applied to various applications such as finance, healthcare, manufacturing, logistics as well as public services. Distributed consensus algorithm is an essential component in blockchain, and it enables all nodes belonging to blockchain network to make an agreement, which means all nodes have the same information. For example, Bitcoin uses a consensus algorithm called Proof-of-Work (PoW) that gives possession of block generation based on the computational volume committed by nodes. However, energy consumption for block generation in PoW has drastically increased due to the growth of computational performance to prove the possession of block. Although many other distributed consensus algorithms including Proof-of-Stake are suggested, they have their own advantages and limitations, and new research works should be proposed to overcome these limitations. For doing this, above all things, we need to establish an evaluation method existing distributed consensus algorithms. Based on this motivation, in this work, we suggest and analyze assessment items by classifying them as efficiency and safety perspectives for investigating existing distributed consensus algorithms. Furthermore, we suggest new assessment criteria and their implementation methods, which can be used for a baseline for improving performance of existing distributed consensus algorithms and designing new consensus algorithm in future.
Mengting Liu, F. Richard Yu, Yinglei Teng, Victor C. M. Leung · 5 authors
Blockchain-based video streaming systems aim to build decentralized peer-to-peer networks with flexible monetization mechanisms for video streaming services. On these blockchain-based platforms, video transcoding, which is computationally intensive and time-consuming, is still a major challenge. Meanwhile, the block size of the underlying blockchain has significant impacts on the system performance. Therefore, this paper proposes a novel blockchain-based framework with an adaptive block size for video streaming with mobile edge computing (MEC). First, we design an incentive mechanism to facilitate collaboration among content creators, video transcoders, and consumers. In addition, we present a block size adaptation scheme for blockchain-based video streaming. Moreover, we consider two offloading modes, i.e., offloading to the nearby MEC nodes or a group of device-to-device (D2D) users, to avoid the overload of MEC nodes. Then, we formulate the issues of resource allocation, scheduling of offloading, and adaptive block size as an optimization problem. We employ a low-complexity alternating direction method of the multipliers-based algorithm to solve the problem in a distributed fashion. Simulation results are presented to show the effectiveness of the proposed scheme.
Jian An, Danwei Liang, Xiaolin Gui, Yang He · 6 authors
With the popularization of intelligent terminals, crowdsensing has become increasingly prominent because of its advantages, such as low cost, high convenience, and fast speed in conducting tasks. However, the quality of the data collected through crowdsensing is varied and is difficult to evaluate. Furthermore, the existing crowdsensing quality control methods are mostly based on a central platform, which is not completely trusted in reality and results in the existence of fraud and other problems. To solve these two questions, a crowdsensing quality control model based on a two-consensus blockchain is proposed in this paper. First, the idea of a blockchain is introduced into this model. The credit-based verifier selection mechanism and the two-consensus approach are proposed to realize the nonrepudiation and nontampering of information in crowdsensing. Then, to help task publishers obtain higher-quality sensing data, the methods of node matching and QGE are proposed. The former method uses the idea of the calculation of matching degree to select workers, and the latter uses the idea of clustering and fuzzy theories to evaluate the quality of the sensing data. Finally, the experiments show that the running time of the block generation in our model is acceptable, and comparing with the other methods, our model can acquire data of higher ioj.
Swarm robotics is a research field in which a group of autonomous robots execute tasks through cooperative works. Sharing information among robots is a central function for an optimal performance of the system. Given that the swarm network structure constantly changes when robots move, it becomes difficult to guarantee on information sharing by all swarm members. We, in this work, propose an approach for information sharing on swarm robotic systems by using Blockchain technology. A function of distributed ledger in Blockchain technology has possibility to solve the information sharing problem and to easily synchronize their state. However, because Blockchain persistently keeps past transactions, the increase of its chain size is one of the serious issues to manage Blockchain technology. In this paper, we introduce a methodology to share information among autonomous robots and demonstrate through experiments that how the differences in data size recorded in the blockchain affect the chain size. As a result, compared with our previous approach, we succeeded in suppressing increase in chain size by using the proposal approach; it was reduced the amount of increase in chain size about 73.0% when each node repeatedly shared about 2.8KB image data by 100 times.
Oct 8, 2018·Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers
Danwei Liang, Jian An, Jindong Cheng, Yang He · 5 authors
In most crowdsensing systems, the quality of the collected data is varied and difficult to evaluate while the existing crowdsensing quality control methods are mostly based on a central platform, which is not completely trusted in reality and results in fraud and other problems. To solve these questions, a novel crowdsensing quality control model is proposed in this paper. First, the idea of blockchain is introduced into this model. The credit-based verifier selection mechanism and twice consensuses are proposed to realize the non-repudiation and non-tampering of information in crowdsensing. Then, the quality grading evaluation (QGE) is put forward, in which the method of truth discovery and the idea of fuzzy theories are combined to evaluate the quality of sensing data, and the garbled circuit is used to ensure that evaluation criteria can not be leaked. Finally, the Experiments show that our model is feasible in time and effective in quality evaluation.
The success of blockchain as the underlying technology for cryptocurrencies has opened up possibilities for its use in other application domains as well. The main advantages of blockchain for its potential use in other domains are its inherent security mechanisms and immunity to different attacks. A blockchain relies on a consensus method for agreeing on any new data. Most of the consensus methods which are currently used for the blockchain of different cryptocurrencies require high computational power and thus are not apt for resource constrained systems.
In this article, we discuss and survey the various blockchain based consensus methods that are applicable to resource constrained IoT devices and networks. A typical IoT network consists of several devices which have limited computational and communications capabilities. Most often, these devices cannot perform the intensive computations and are starved for bandwidth. Therefore, we discuss the possible measures that can be taken to reduce the computational power and convergence time for the underlying consensus methods. We also discuss some of the alternatives to the public blockchain like private blockchain and tangle, and their potential adoption for IoT networks. Furthermore, we discuss the existing consensus methods and blockchain implementations and explore the possibility of utilizing them to realize a blockchain based IoT network. Some of the open research challenges are also put forward.
This paper proposes a JPEG-blockchain framework for trusted media transaction. The new distributed and tamperproof framework intends to aid an emerging JPEG Privacy and Security standard. The blockchain network records any media transaction with necessary information related to intellectual property rights, access control rules and content signature. The content signature, generated by compressed sensed samples or low-resolution, low bit-rate compression is used to verify the image integrity and authenticity. We propose that every blockchian record, linked to a unique transaction hash, is encapsulated within the metadata contained in the JPEG box structure. As an example use case we have chosen the GLAM (Galleries, Libraries, Archives and Museums) sector due to its emerging need. This paper presents the proof of the concept and reports preliminary infrastructural development.
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Blockchain technology has the characteristics of decentralization, security and non-modifiable. The consensus algorithm is the core of blockchain framework, which solves the problem of mutual trust among nodes in the distributed network. Selecting the appropriate consensus algorithm or not directly affects the performance of blockchain. However, existing private blockchain platform lacks theory and data support for the performance analysis of the consensus algorithm. This paper proposes a method to evaluate the performance of consensus algorithm in private blockchain platforms of Ethereum and Hyperledger Fabric. Through quantitative analysis of latency and throughput, we obtain the performance evaluation results of consensus algorithms with different numbers of transactions. The results show that the consensus mechanism induces performance bottleneck. Besides, Practical Byzantine Fault Tolerance (PBFT) consistently outperforms Proof-of-Work (PoW) in terms of latency and throughput under varying workloads. This paper contributes to providing not only the quantitative data support for the further research of consensus algorithm, but also the guidance to the blockchain practitioners in the selection of consensus mechanism.