Tell the Smart House to Mind its Own Business!: Maintaining Privacy and Security in the Era of Smart Devices

Consumers want convenience. That convenience often comes in the form of everyday smart devices that connect to the internet and assist with daily tasks. With the advancement of technology and the “Internet of Things” in recent years, convenience is at our fingertips more than ever before. Not only do consumers want convenience, they want to trust that their product is performing the task that they purchased it for and not exposing them to danger or risk. However, due to the increasing capabilities and capacities of smart devices, consumers are less likely to realize the implications of what they are agreeing to when they purchase and begin using these products. This Note will focus on the risks associated with smart devices, using smart home devices as an illustration. These devices have the ability to collect intimate details about the layout of the home and about those who live within it. The mere collection of this personal data opens consumers up to the risk of having their private information shared with unintended recipients whether the information is being sold to a third party or accessible to a hacker. Thus, to adequately protect consumers, it is imperative that they can fully consent to their data being collected, retained, and potentially distributed. This Note examines the law that is currently in place to protect consumers who use smart devices and argues that a void ultimately leaves consumers vulnerable. Current data privacy protection in the United States centers on the self-regulatory regime of “notice and choice.” This Note highlights how the self-regulatory notice-and-choice model fails to ensure sufficient protection for consumers who use smart devices and discusses the need for greater privacy protection in the era of the emerging Internet of Things. Ultimately, this Note proposes a state-level resolution and calls upon an exemplar state to experiment with privacy protection laws to determine the best way to regulate the Internet of Things

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

Decentralized brokered enabled ecosystem for data marketplace in smart cities towards a data sharing economy

Presently data are indispensably important as cities consider data as a commodity which can be traded to earn revenues. In urban environment, data generated from internet of things devices, smart meters, smart sensors, etc. can provide a new source of income for citizens and enterprises who are data owners. These data can be traded as digital assets. To support such trading digital data marketplaces have emerged. Data marketplaces promote a data sharing economy which is crucial for provision of available data useful for cities which aims to develop data driven services. But currently existing data marketplaces are mostly inadequate due to several issues such as security, efficiency, and adherence to privacy regulations. Likewise, there is no consolidated understanding of how to achieve trust and fairness among data owners and data sellers when trading data. Therefore, this study presents the design of an ecosystem which comprises of a distributed ledger technology data marketplace enabled by message queueing telemetry transport (MQTT) to facilitate trust and fairness among data owners and data sellers. The designed ecosystem for data marketplaces is powered by IOTA technology and MQTT broker to support the trading of sdata sources by automating trade agreements, negotiations and payment settlement between data producers/sellers and data consumers/buyers. Overall, findings from this article discuss the issues associated in developing a decentralized data marketplace for smart cities suggesting recommendations to enhance the deployment of decentralized and distributed data marketplaces.publishedVersio

Energy-aware Demand Selection and Allocation for Real-time IoT Data Trading

Personal IoT data is a new economic asset that individuals can trade to generate revenue on the emerging data marketplaces. Typically, marketplaces are centralized systems that raise concerns of privacy, single point of failure, little transparency and involve trusted intermediaries to be fair. Furthermore, the battery-operated IoT devices limit the amount of IoT data to be traded in real-time that affects buyer/seller satisfaction and hence, impacting the sustainability and usability of such a marketplace. This work proposes to utilize blockchain technology to realize a trusted and transparent decentralized marketplace for contract compliance for trading IoT data streams generated by battery-operated IoT devices in real-time. The contribution of this paper is two-fold: (1) we propose an autonomous blockchain-based marketplace equipped with essential functionalities such as agreement framework, pricing model and rating mechanism to create an effective marketplace framework without involving a mediator, (2) we propose a mechanism for selection and allocation of buyers' demands on seller's devices under quality and battery constraints. We present a proof-of-concept implementation in Ethereum to demonstrate the feasibility of the framework. We investigated the impact of buyer's demand on the battery drainage of the IoT devices under different scenarios through extensive simulations. Our results show that this approach is viable and benefits the seller and buyer for creating a sustainable marketplace model for trading IoT data in real-time from battery-powered IoT devices.Comment: Accepted in SmartComp 202

Cost-effective blockchain-based IoT data marketplaces with a credit invariant

Billions of Internet of Things (IoT) devices deployed today collect massive amounts of potentially valuable data. To efficiently utilize this data, markets must be developed where data can be traded in real time. Blockchain technology offers a potential platform for these types of markets. However, previous proposals using blockchain technology either require trusted third parties such as data brokers, or necessitate a large number of on-chain transactions to operate, incurring excessive overhead costs. This paper proposes a trustless data trading system that minimizes both the risk of fraud and the number of transactions performed on chain. In this system, data producers and consumers come to binding agreements while trading data off chain and they only settle on chain when a deposit or withdrawal of funds is required. A credit mechanism is also developed to further reduce the incurred fees. Additionally, the proposed marketplace is benchmarked on a private Ethereum network running on a lab-scale testbed and the proposed credit system is simulated so to analyze its risks and benefits

Ensuring Personal Data Anonymity in Data Marketplaces through Sensing-as-a-Service and Distributed Ledger

Personal data has undoubtedly assumed a great value with the advancements on technologies able to gather it and infer from it. The businesses that operate in a data-driven economy offer services that rely on data collected about their users and usually they store this personal information in \u201csilos\u201d that impede transparency on their use and possibilities of easy interactions. The introduction in EU of the General Data Protection Regulation (GDPR) moves this economy towards a user-centered vision, in which individuals have rights for their data sovereignty and the free portability of it. However, more efforts are needed to reach both transparency and balance between privacy and data sharing. In this paper, we present a solution to promote the development of personal data marketplaces, exploiting the use of Distributed Ledger Technologies (DLTs) and a Sensing-as-a-Service (SaaS) model, in order to enhance the privacy of individuals, following the principles of personal data sovereignty and interoperability. Moreover, we provide experimental results of an implementation based on IOTA, a promising DLT for managing and transacting IoT dat

Weathering the Nest: Privacy Implications of Home Monitoring for the Aging American Population

The research in this paper will seek to ascertain the extent of personal data entry and collection required to enjoy at least the minimal promised benefits of distributed intelligence and monitoring in the home. Particular attention will be given to the abilities and sensitivities of the population most likely to need these devices, notably the elderly and disabled. The paper will then evaluate whether existing legal limitations on the collection, maintenance, and use of such data are applicable to devices currently in use in the home environment and whether such regulations effectively protect privacy. Finally, given appropriate policy parameters, the paper will offer proposals to effectuate reasonable and practical privacy-protective solutions for developers and consumers