Mobile Crowd‐Sensing for Smart Cities

Song, Houbing; Srinivasan, Ravi; Sookoor, Tamim; Jeschke, Sabina

doi:10.1002/9781119226444.ch5

Cited by 19 publications

(5 citation statements)

References 45 publications

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“…From the user’s perspective, security and privacy is a major concern in MCS, especially as MCS applications mostly gather sensitive sensor data of users which can be used to infer behavioural patterns of participants [19]. This makes it necessary to analyze potential disclosure of such sensitive information of users by sensing applications [28].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Reliability of users in MCS can be sustained through incentive mechanisms as users tend to submit reliable data when good incentives are offered. Incentive mechanism is designed to inspire active human participation in MCS [19].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Data trustworthiness is a major concern in mobile crowd sensing, since acquired data is mostly used for decision making that affects the quality of life of citizens [18]. Also, user trustworthiness refers to the average reputation of a user over a certain period of time [19]. Data trustworthiness in user incentivization was studied in Kantarci et al [20].…”

Section: Data Trustworthiness and User Reputationmentioning

confidence: 99%

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Security analysis of mobile crowd sensing applications

Owoh

Singh

2020

ACI

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The proliferation of mobile phones with integrated sensors makes large scale sensing possible at low cost. During mobile sensing, data mostly contain sensitive information of users such as their real-time location. When such information are not effectively secured, users’ privacy can be violated due to eavesdropping and information disclosure. In this paper, we demonstrated the possibility of unauthorized access to location information of a user during sensing due to the ineffective security mechanisms in most sensing applications. We analyzed 40 apps downloaded from Google Play Store and results showed a 100% success rate in traffic interception and disclosure of sensitive information of users. As a countermeasure, a security scheme which ensures encryption and authentication of sensed data using Advanced Encryption Standard 256-Galois Counter Mode was proposed. End-to-end security of location and motion data from smartphone sensors are ensured using the proposed security scheme. Security analysis of the proposed scheme showed it to be effective in protecting Android based sensor data against eavesdropping, information disclosure and data modification.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Data Trustworthiness and User Reputationmentioning

confidence: 99%

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Security analysis of mobile crowd sensing applications

Owoh

Singh

2020

ACI

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“…Comunicação: devido a restrita capacidade computacional de alguns dispositivos, a aplicação de proteções de privacidade durante a comunicação ainda é um desafio [2]. Identificamos dois requisitos referentes a comunicação.…”

Section: Dimensão: Tecnologiasunclassified

Requisitos de Privacidade para Aplicações de Crowdsourcing no Contexto das Cidades Inteligentes

Silva¹,

Viterbo²,

Bernardini³

et al. 2019

Anais Estendidos Do Simpósio Brasileiro De Fatores Humanos Em Sistemas Computacionais (IHC)

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As tecnologias são parte integrante do funcionamento das cidades inteligentes, sendo aplicadas em muitas áreas, como: saúde, mobilidade, serviços públicos etc. O uso de tecnologias, como crowdsourcing, permite as pessoas colaborarem na criação e aprimoramento dos produtos e serviços das cidades e pode ser amplamente utilizado. No entanto, o uso dessas informações pode causar problemas de privacidade para os usuários. Para fornecer proteção adequada às informações é necessário primeiro definir os requisitos envolvidos. Identificamos a partir de uma revisão de literatura os principais requisitos de privacidade. Esses requisitos foram observados em estudos de privacidade abrangendo o uso de crowdsourcing no contexto de cidades inteligentes e as novas legislações de privacidade.

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“…With the proliferation of intelligent sensing devices such as cameras, accelerometers, GPSs, etc., and the ongoing expansion of mobile network capabilities, crowdsensing could contribute significantly to the development of the Internet of Things (IoT). This could see crowdsensing applied to transportation [4,5], smart city [6], water-quality monitoring [7], pollution measurement [8,9], human location [10], etc.…”

Section: Introductionmentioning

confidence: 99%

A Blockchain-Based Hybrid Incentive Model for Crowdsensing

Wei

Long

2020

Electronics

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Crowdsensing is an emerging paradigm of data aggregation, which has a pivotal role in data-driven applications. By leveraging the recruitment, a crowdsensing system collects a large amount of data from mobile devices at a low cost. The critical issues in the development of crowdsensing are platform security, privacy protection, and incentive. However, the existing centralized, platform-based approaches suffer from the single point of failure which may result in data leakage. Besides, few previous studies have addressed the considerations of both the economic incentive and data quality. In this paper, we propose a decentralized crowdsensing architecture based on blockchain technology which will help improve the attack resistance. Furthermore, we present a hybrid incentive mechanism, which integrates the data quality, reputation, and monetary factors to encourage participants to contribute their sensing data while discouraging malicious behaviors. The effectiveness our of proposed incentive model is verified through a combination of the theory of mechanism design. The performance analysis and simulation results illustrate that the proposed hybrid incentive model is a reliable and efficient mean to promote data security and incentivizing positive conduct on the crowdsensing application.

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Mobile Crowd‐Sensing for Smart Cities

Cited by 19 publications

References 45 publications

Security analysis of mobile crowd sensing applications

Security analysis of mobile crowd sensing applications

Requisitos de Privacidade para Aplicações de Crowdsourcing no Contexto das Cidades Inteligentes

A Blockchain-Based Hybrid Incentive Model for Crowdsensing

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