Aug 1, 2020·2020 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech)
People aged 65 and above are considered to be the fastest-growing population in the world. It is believed that the majority of elderly people will be living alone and hence need to receive health services to ensure their well-being. One promising way is to provide caregivers access to the elderly daily activities (e.g., eating, cleaning, exercising patterns, etc.) through non-intrusive means. Therefore, recognizing and tracking their daily activities play a key role in providing timely health and emergency services that foster better day-to-day care. The solution proposed in this paper is based on analyzing and recognizing the daily activities based on the energy consumption of appliances inside homes. To ensure that elderly people's data are protected and accessible by authorized personnel within the healthcare ecosystem, blockchain technology is used as a means for maintaining and sharing daily activities patterns with healthcare providers. The main challenges of this paper are as follows: (i) How to recognize relationships between appliance usage and daily activities from concurrent streams of smart meter data; and (ii) how to construct profiles of daily activities and upload them to the blockchain system. For addressing these issues, we develop our model based on Bayesian network to recognize daily activities based on the energy consumption of appliances. To ensure that elderly people's data are protected, we use Hyperledger blockchain technology as a trustworthy mechanism for creating profiles, in order to protect data and prevent scams or frauds that might jeopardize people's privacy.
Web-based public participatory GIS (PPGIS) has been used by governmental organizations to facilitate people's contribution to decision-making processes. However, these applications do not provide an open and transparent environment for public participation. This study suggests that PPGISs should be developed as decentralized applications (DApp) based on Ethereum blockchain technology to have a fully open, transparent, and accountable environment for public participation. In a blockchain-based PPGIS, the collected data are securely saved on the blockchain. The validity of the data, replicated on the nodes of the peer-to-peer blockchain network, is ensured through a consensus process without any central control. The data is tamper-free and immutable. Additionally, the data is openly accessible to institutions and citizens. A prototype PPGIS was developed as a DApp through which users can participate in the site selection of urban facilities. Using the application, they compare and rank different criteria. The system solves an analytic hierarchy process to calculate the weights of the criteria. A suitability map is generated afterward and published to be used by both citizens and decision-makers. The feasibility of the application, along with the issues that need to be considered while using blockchain technology for urban planning and development, are thoroughly discussed.
Emanuel Vieira, Paulo Bartolomeu, Seyed M. Hosseini, Joaquim Ferreira
The extensive use of smartphones combined with the rise in the Internet of Things adoption has fostered the emergence of several use-cases to provide added comfort and peace of mind in our everyday life. Public transportation payment in large cities, where frequent commuters and generic users often spend a significant amount of time buying and validating tickets, can become a cumbersome process. This paper presents the design and implementation of a seamless payment system named IOTApass, which handles payments through the usage of a smartphone and a distributed ledger technology to avoid the limitations of centralized payment solutions. The IOTApass enables a user to seamlessly pay for public transports using a smartphone App without explicit (user) interface interactions, thus reducing payment complexity. Besides describing the architecture, operation, and implementation of IOTApass, the paper documents its experimental validation and confirms its feasibility.
In order to contain the COVID-19 pandemic, several countries enforced extended social distancing measures for several weeks, effectively pausing the majority of economic activities. In an effort to resume economic activity safely, several Digital Contact Tracing applications and protocols have been introduced with success. However, DCT is a reactive method, as it aims to break existing chains of disease transmission in a population. Therefore DCT is not suitable for proactively preventing the spread of a disease; an approach that relevant to certain use cases, such as international tourism, where individuals travel across borders. In this work, we first identify the limitations characterising DCT related to privacy issues, unwillingness of the public to use DCT mobile apps due to privacy concerns, lack of interoperability among different DCT applications and protocols, and the assumption that there is limited, local mobility in the population. We then discuss the concept of a Health Passport as a means of verifying that individuals are disease risk-free and how it could be used to resume the international tourism sector. Following, we present the DHP Framework that uses a private blockchain and Proof of Authority for issuing Digital Health Passports. The framework provides a distributed infrastructure supporting the issuance of DHPs by foreign health systems and their verification by relevant stakeholders, such as airline companies and border control authorities. We discuss the attributes of the system in terms of its usability and performance, security and privacy. Finally, we conclude by identifying future extensions of our work on formal security and privacy properties that need to be rigorously guaranteed via appropriate security protocols.
Alexandros Bampoulidis, A. Bruni, Lukas Helminger, Daniel Kales · 6 authors
Recent work has shown that cell phone mobility data has the unique potential to create accurate models for human mobility and consequently the spread of infected diseases [74]. While prior studies have exclusively relied on a mobile network operator’s subscribers’ aggregated data in modelling disease dynamics, it may be preferable to contemplate aggregated mobility data of infected individuals only. Clearly, naively linking mobile phone data with health records would violate privacy by either allowing to track mobility patterns of infected individuals, leak information on who is infected, or both. This work aims to develop a solution that reports the aggregated mobile phone location data of infected individuals while still maintaining compliance with privacy expectations. To achieve privacy, we use homomorphic encryption, validation techniques derived from zero-knowledge proofs, and differential privacy. Our protocol’s open-source implementation can process eight million subscribers in 70 minutes.
Alexandros Bampoulidis, A. Bruni, Lukas Helminger, Daniel Kales · 6 authors
Recent work has shown that cell phone mobility data has the unique potential\nto create accurate models for human mobility and consequently the spread of\ninfected diseases. While prior studies have exclusively relied on a mobile\nnetwork operator's subscribers' aggregated data in modelling disease dynamics,\nit may be preferable to contemplate aggregated mobility data of infected\nindividuals only. Clearly, naively linking mobile phone data with health\nrecords would violate privacy by either allowing to track mobility patterns of\ninfected individuals, leak information on who is infected, or both. This work\naims to develop a solution that reports the aggregated mobile phone location\ndata of infected individuals while still maintaining compliance with privacy\nexpectations. To achieve privacy, we use homomorphic encryption, validation\ntechniques derived from zero-knowledge proofs, and differential privacy. Our\nprotocol's open-source implementation can process eight million subscribers in\n70 minutes.\n
The COVID-19 pandemic has imposed numerous, lasting adverse effects on the global tourism industry. At the same time, it exposed the competitive advantages that existing smart tourism infrastructure could provide for addressing urgent health issues and providing meaningful smart services. This paper initially provides examples of smart geospatial services based on COVID-19 pandemic-related data, such as algorithms for measuring social distancing through CCTV and proximity contract tracing protocols and applications. Indeed, smart destinations, as an evolutionary step of smart cities, very quickly became a practical and research framework in various other disciplines, from leisure and service-oriented to technical and geospatial domains. However, various technologies employed and interests of different stockholders create a constant need for rescaling of smart data to facilitate their usability in providing optimized smart tourism services. One of the pressing concerns is the functional alignment of geospatial data with tourism-related data. Thus, we aim to pinpoint the growing importance of smart geospatial services, by pointing to the main downturn of the current smart destination issue with geospatial data resolutions, and, by building upon the relations of the geospatial layer of data with the tourism-specific layer. To this end, we pinpoint two further research directions - reinvestigating spatial and temporal resolution as a core of data smartness and the need for contextual (tourism-oriented) scaling of smart technology. This could be of keen interest in post-pandemic tourism, where smart geospatial services will be of pressing concern, but also it still an issue to be resolved in further smart destination development.
This paper presents the design and implementation of a smart home system in the context of Internet of Things (IoT) with Ethereum private Blockchain, Raspberry Pi, Blynk platform, DHT11 temperature and humidity sensors. By Raspberry Pi, it collects real-time room humidity and temperature information by DHT11. The data is then uploaded to the Blynk App, which is stored on the smart contract deployed with the Ethereum private Blockchain. When the real-time humidity or temperature value exceeds a predefined threshold value, warnings are given by turning on LEDs. The system functions as a proof-of-concept prototype, showing the feasibility of applying blockchain in smart homes with IoT functionalities.
Smart cities can deliver innovative solutions by leveraging technologies such as Internet of Things(IoT) and Blockchains. Driver profiling is of paramount importance in smart cities to monitor driving patterns, traffic violations, and resolve legal issues. However, preserving confidentiality of driver records while continuously monitoring their activities is a major challenge. Traditional mechanisms for driver profiling involve manual intervention and has a higher risk of exposure to being tampered. Thus it becomes necessary to equip smart cities with a tamper-resistant and a decentralized driver profiling system which is capable of storing driver records. In this work, we propose a Blockchain based framework for driver profiling in smart cities which enables secure collection and storage of driver and event records. The framework is composed of various services such as: 1) Driver registration and identity validation using Authentication service 2) Provide driver with a unique time-based token for recording event based data to ensure data authenticity. Finally, we evaluate the system by measuring the performance and power consumption and analyzing power-performance trade-offs. Our proposed framework is generic in that it can be utilized by online transportation networks for driver behavior tracking and profiling.
A startling announcement came on a crisp, fall day in 2017: Sidewalk Labs, a sister company of Google, was awarded a contract to create a ‘smart city’ along a small stretch of Toronto’s largely con...
Yao Sun, Lei Zhang, Gang Feng, Bowen Yang · 6 authors
Blockchain has shown a great potential for Internet of Things (IoT) systems to establish trust and consensus mechanisms with no involvement of any third party. It has been not clear how the low complexity devices and the wireless communications among them can pose constraints on the blockchain enabled IoT systems. In this paper, we establish a fundamental analysis model to underpin the blockchain enabled IoT system. By considering spatio-temporal domain Poisson distribution, i.e., node geographical distribution and transaction arrival rate in time domain are both modeled as Poisson point process (PPP), we first derive the distribution of signal-to-interference-plus-noise ratio (SINR), blockchain transaction successful rate as well as overall throughput. Then, based on the analytical model, we design an optimal full function node deployment for blockchain system to achieve the maximum transaction throughput with the minimum full function node density. Numerical results validate the accuracy of our theoretical analysis and evaluate the relationship between blockchain full function node deployment and the density of IoT nodes.
We exploit the public good attributes of information and communication technologies (ICTs) and theoretically analyze an aggregate economy of two smart cities in which ICTs are provided in either a decentralized or a centralized manner. We first determine the efficient ICT levels that maximize the aggregate surplus from the provision of ICTs in the two cities. Second, we compute the optimal level of ICT provision in the two cities in a decentralized regime in which spending on the ICTs is financed by a uniform tax on the city residents. Third, we ascertain the optimal level of ICT provision in the two cities in a centralized regime subject to equal provision of ICTs and cost sharing. Fourth, we show that if the two cities have the same preference for ICTs then centralization is preferable to decentralization as long as there is a spillover from the provision of ICTs. Finally, we show that if the two cities have dissimilar preferences for ICTs then centralization is preferable to decentralization as long as the spillover exceeds a certain threshold.
Mobile crowdsensing(MCS) is an emerging pattern which means task initiators attract mobile users sensing with their own devices by some platforms. MCS could exploit idle resources in low cost, while it has lots of flaws, which impede its developments. First, isolations between different MCS systems leads to wastage of social resources. What's more, current MCS always operate in a centralized way, which causes it vulnerable and unbelievable. Blockchain is a promising technology which could supply a credible and transparent environment. This paper construct a blockchain based MCS market and design smart contract for its operation. In our design, platform breaks isolation by blockchain, task initiators and mobile users manage their tasks by smart contract and bargain price with distributed algorithm. By this way, resource could be exploited better, and the market could be more fair. What's more, the paper analyzes Walrasian Equilibrium (WE) in the market, and details how to deploy MCS in blockchain. Evalution results shows that Equilibrium could be found.
Mohamad Arafeh, May El Barachi, Azzam Mourad, Fatna Belqasmi
With the emergence of mobile crowdsensing (MCS), we now have the possibility of leveraging the sensing capabilities of mobile devices to collect information and intelligence about cities and events. Despite the promise that MCS brings, this new concept opens the door to a multitude of security and privacy threats and attacks. Indeed, the human involvement in the crowdsensing process and the openness of this process to any participant, render the task of securing MCS environments very challenging. In this work, we propose a Blockchain-based hybrid architecture for the detection and prevention of fake sensing activities in MCS. Our architecture leverages the capabilities of the Blockchain network and introduces a new role to the MCS architecture to ensure the validation of the collected information. Combining both data quality metrics along with behavioral analysis based participants' reliability scoring, our solution is able to detect variations in behavior and quality of contributions. The proposed solution was tested with real life data collected from 200 mobile users, over the span of 2 years, and the results obtained are very promising.
Roman Overko, Rodrigo Ordóñez-Hurtado, Sergiy Zhuk, Pietro Ferraro · 6 authors
We introduce a permissioned distributed ledger technology (DLT) design for crowdsourced smart mobility applications. This architecture is based on a directed acyclic graph architecture (similar to the IOTA tangle) and uses both Proof-of-Work and Proof-of-Position mechanisms to provide protection against spam attacks and malevolent actors. In addition to enabling individuals to retain ownership of their data and to monetize it, the architecture also is suitable for distributed privacy-preserving machine learning algorithms, is lightweight, and can be implemented in simple internet-of-things (IoT) devices. To demonstrate its efficacy, we apply this framework to reinforcement learning settings where a third party is interested in acquiring information from agents. In particular, one may be interested in sampling an unknown vehicular traffic flow in a city, using a DLT-type architecture and without perturbing the density, with the idea of realizing a set of virtual tokens as surrogates of real vehicles to explore geographical areas of interest. These tokens, whose authenticated position determines write access to the ledger, are thus used to emulate the probing actions of commanded (real) vehicles on a given planned route by "jumping" from a passing-by vehicle to another to complete the planned trajectory. Consequently, the environment stays unaffected (i.e., the autonomy of participating vehicles is not influenced by the algorithm), regardless of the number of emitted tokens. The design of such a DLT architecture is presented, and numerical results from large-scale simulations are provided to validate the proposed approach.
In this paper, we investigate people’s perception of datafication and surveillance in Amsterdam Smart City. Based on a series of focus groups, we show how people understand new forms of hypervisbility, what strategies they use to navigate these experiences, and what the limitations of these strategies are. We show how people tried to discern between public and private sector actors, to differentiate who they trusted by building on the existing social contract. People also trusted the objectivity of data in relation to prior experiences of social contexts and discrimination. Lastly, we show how the experiences of some of the inhabitants in our study who were most vulnerable to hypervisibility highlight the limits to strategies based on the neutrality of data. By asking about perceived surveillance rather than emphasising actual practices of surveilling, we show differentiated contexts and strategies, providing empirical grounds to question the dominant technical framing of smart cities.
International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Data protection is about protecting information about per-sons, which is currently flowing without much control –individuals can-not easily exercise the rights granted by the EU General Data Protection Regulation (GDPR). Individuals benefit from “free” services offered by companies in exchange of their data, but these companies keep their users’ data in “silos” that impede transparency on their use and possibilities of easy interactions. The introduction of the GDPR warrants control rights to individuals and the free portability of personal data from one entity to another. However it is still beyond the individual’s capability to perceive whether their data is managed in compliance with GDPR. To this regard, in this work the proposed approach consists in using decentralized mechanisms to provide transparency through distributed ledgers, data flow governance by using smart contracts and interoperability relying on semantic web technologies.