Privacy in Internet of Things: From Principles to Technologies

Li, Chao; Palanisamy, Balaji

doi:10.1109/jiot.2018.2864168

Cited by 94 publications

(27 citation statements)

References 126 publications

(169 reference statements)

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“…It is believed that every person should have the right to control his/her private data [62]. The term of information privacy or data privacy was known since the 1960s, due to the increase of electronic data processing [91]. Privacy was defined as "the right to be let alone", by Warren and Brandeis in 1890, in his article of 'The Right to privacy' [92].…”

Section: Security and Privacy In The Internet Of Thingsmentioning

confidence: 99%

Systematic Review of Existing IoT Architectures Security and Privacy Issues and Concerns

Alshohoumi¹,

Sarrab²,

AlHamadani³

et al. 2019

IJACSA

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Internet of things (IoT) has become one of the most prominent technologies that the world has been witnessing nowadays. It provides great solutions to humanity in many significant fields of life. IoT refers to a collection of sensors or object in the universe with the capability of communicating with each other through the internet without human intervention. Currently, there is no standard IoT architecture. As it is in its infancy, IoT is surrounded by numerous security and privacy concerns. Thus, to avoid such concerns that may hinder its deployment, an IoT architecture has to be carefully designed to incorporate security and privacy solutions. In this paper, a systematic literature review was conducted to trace the evolvement of IoT architectures from its initial development in 2008 until 2018. The Comparison among these architectures is based on terms of the architectural stack, covered issues, the technology used and considerations of security and privacy aspects. The findings of the review show that the initial IoT architectures did not provide a comprehensive meaning for IoT that describe its nature, whereas the recent IoT architectures convey a comprehensive meaning of IoT, starting from data collection, followed by data transmission and processing, and ending with data dissemination. Moreover, the findings reveal that IoT architecture has evolved gradually across the years, through improving architecture stack with new solutions to mitigate IoT challenges such as scalability, interoperability, extensibility, management, etc. with lack consideration of security solutions. The findings disclose that none of the discussed IoT architectures considers privacy concerns, which indeed considered as a critical factor of IoT sustainability and success. Therefore, there is an inevitable need to consider security and privacy solutions when designing IoT architecture.

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Section: Security and Privacy In The Internet Of Thingsmentioning

confidence: 99%

Systematic Review of Existing IoT Architectures Security and Privacy Issues and Concerns

Alshohoumi¹,

Sarrab²,

AlHamadani³

et al. 2019

IJACSA

View full text Add to dashboard Cite

show abstract

“…A comprehensive review of the state of the art related to IoT architectures, Privacy Enhancing Technologies (PETs), and privacy laws was carried out in [15]. It was identified that implementing PETs at various layers of IoT architecture could ensure the privacy needs.…”

Section: Background Studymentioning

confidence: 99%

CATSWoTS: Context Aware Trustworthy Social Web of Things System

Javaid

Afzal

Arif

et al. 2019

Sensors

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The inevitable revolution of the Internet of Things (IoT) and its benefits can be witnessed everywhere. Two major issues related to IoT are the interoperability and the identification of trustworthy things. The proposed Context-Aware Trustworthy Social Web of Things System (CATSWoTS) addresses the interoperability issue by incorporating web technologies including Service Oriented Architecture where each thing plays the role of a service provider as well as a role of service consumer. The aspect of social web helps in getting recommendations from social relations. It was identified that the context dependency of trust along with Quality of Service (QoS) criteria, for identifying and recommending trustworthy Web of Things (WoT), require more attention. For this purpose, the parameters of context awareness and the constraints of QoS are considered. The research focuses on the idea of a user-centric system where the profiles of each thing (level of trustworthiness) are being maintained at a centralized level and at a distributed level as well. The CATSWoTS evaluates service providers based on the mentioned parameters and the constraints and then identifies a suitable service provider. For this, a rule-based collaborative filtering approach is used. The efficacy of CATSWoTS is evaluated with a specifically designed environment using a real QoS data set. The results showed that the proposed novel technique fills the gap present in the state of the art. It performed well by dynamically identifying and recommending trustworthy services as per the requirements of a service seeker.

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“…In keeping with this trend, today, IoT data markets can be categorized into two major approaches regarding privacy [11]: i) privacy protection market and ii) privacy valuation market. In the privacy protection market, privacy-enhancing technologies are provided to data providers, which minimize potential privacy infringement risks and protect possible privacy violations caused by IoT services/applications [12], [13]. On the other hand, in the privacy valuation market, data brokers offer proper benefits or incentives to data providers (who consider the value between privacy protection and valuation) for collecting IoT datasets under agreement or consent.…”

Section: Introductionmentioning

confidence: 99%

Competitive Data Trading Model With Privacy Valuation for Multiple Stakeholders in IoT Data Markets

Park

Lee

et al. 2020

IEEE Internet Things J.

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With the widespread of Internet of Things (IoT) environment, a big data concept has emerged to handle a large number of data generated by IoT devices. Moreover, since datadriven approaches now become important for business, IoT data markets have emerged, and IoT big data are exploited by major stakeholders such as data brokers and data service providers. Since many services and applications utilize data analytic methods with collected data from IoT devices, the conflict issues between privacy and data exploitation are raised, and the markets are mainly categorized as privacy protection markets and privacy valuation markets, respectively. Since these kinds of data value chains (which are mainly considered by business stakeholders) are revealed, data providers are interested in proper incentives in exchange for their privacy (i.e., privacy valuation) under their agreement. Therefore, this paper proposes a competitive data trading model that consists of data providers who weigh the value between privacy protection and valuation as well as other business stakeholders. Each data broker considers the willingness-to-sell of data providers, and a single data service provider considers the willingness-to-pay of service consumers. At the same time, multiple data brokers compete to sell their dataset to the data service provider as a non-cooperative game model. Based on the Nash Equilibrium analysis (NE) of the game, the feasibility is shown that the proposed model has the unique NE that maximizes the profits of business stakeholders while satisfying all market participants.

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Privacy in Internet of Things: From Principles to Technologies

Cited by 94 publications

References 126 publications

Systematic Review of Existing IoT Architectures Security and Privacy Issues and Concerns

Systematic Review of Existing IoT Architectures Security and Privacy Issues and Concerns

CATSWoTS: Context Aware Trustworthy Social Web of Things System

Competitive Data Trading Model With Privacy Valuation for Multiple Stakeholders in IoT Data Markets

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