Efficient and privacy-preserving access to sensor data for Internet of Things (IoT) based services

Appavoo, Paramasiven; Chan, Mun Choon; Bhojan, Anand; Chang, Ee-Chien

doi:10.1109/comsnets.2016.7439941

Cited by 13 publications

(21 citation statements)

References 21 publications

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“…In Appavoo, Chan, Bhojan, and Chang (2016),a lightweight functional encryption for privacy-preservation based on trust model was proposed. The proposed approach aims to minimize privacy loss and secondary uses in the presence of untrusted parties.…”

Section: Privacy Issues In Iotmentioning

confidence: 99%

Internet of Things and data mining: From applications to techniques and systems

Gaber

Aneiba

Basurra

et al. 2018

WIREs Data Min & Knowl

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The Internet of Things (IoT) is the result of the convergence of sensing, computing, and networking technologies, allowing devices of varying sizes and computational capabilities (things) to intercommunicate. This communication can be achieved locally enabling what is known as edge and fog computing, or through the well‐established Internet infrastructure, exploiting the computational resources in the cloud. The IoT paradigm enables a new breed of applications in various areas including health care, energy management and smart cities. This paper starts off with reviewing these applications and their potential benefits. Challenges facing the realization of such applications are then discussed. The sheer amount of data stemmed from devices forming the IoT requires new data mining systems and techniques that are discussed and categorized later in this paper. Finally, the paper is concluded with future research directions. This article is categorized under: Fundamental Concepts of Data and Knowledge > Big Data Mining Application Areas > Health Care Application Areas > Industry Specific Applications

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Section: Privacy Issues In Iotmentioning

confidence: 99%

Internet of Things and data mining: From applications to techniques and systems

Gaber

Aneiba

Basurra

et al. 2018

WIREs Data Min & Knowl

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“…In [9] proposed a lightweight privacy-preserving trust model based on the observation that a large class of applications can be provisioned based on simple threshold detection. The main algorithm in this proposed model is an uniformization scheme that uses a combination of sensor aliases to hide the identity of the sensing source and perfunction initialization vector to reveal information only to relevant service providers.…”

Section: Related Workmentioning

confidence: 99%

“…First, processing on sensor is minimum and can Using Smart Contract for Privacy Preserving in Internet of Things (IoT) Environments be easily implemented on resource constrained device [9]. Second, since the data store and service provider are separate entities, service provisioning is now open to external third party providers and a user have the flexibility to dynamically configure the service he/she wants [9]. We use proposed model in [9] and its functions for generating shared keys in our proposed protocol.…”

Section: Related Workmentioning

confidence: 99%

Using Smart Contract for Privacy Preserving in Internet of Things (IoT) Environments

Dehrouyeh¹,

Azmi²

2018

JACN

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 Abstract-The utilization of IoT technology increases uninterrupted. The sensors in IoT environments collect great amounts of data and give them to the service providers. This generous content of user's individual data for IoT applications introduces new security challenges. Indeed privacy preserving is a very significant issue for IoT applications. In this paper, we propose a protocol for privacy preserving in IoT environments using blockchain technology and smart contract concept. Blockchain provides a condition that non-trusting members can correlate with each other without a trusted intermediary. Smart contract is a computer code that executes the conditions of a contract itself. Smart contract helps us to exchange our valuable things in a transparent way without any need to a middleman. The key issue in this work is a secure transmission of the shared key between a sender and a receiver using smart contract and blockchain technology in IoT environments. The secure exchange of shared key can result privacy preserving. We have implemented a prototype of the proposed protocol using pyethereum, and evaluate its security via AVISPA tool.

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“…Several recent researches have been conducted for the privacy-preserving for the IoT based services [28][29][30][31][32][33][34][35][36]. In order to handle the massive amount of data, the most convincing solution is the federation of the IoT and cloud computing.…”

Section: Privacy-preserving For Iotmentioning

confidence: 99%

“…The authors in [29] proposed PAgIoT, a Privacy preserving Aggregation protocol suitable for IoT settings and enables multi-attribute aggregation for groups of entities while allowing for privacy-preserving value correlation. A lightweight privacy-preserving trust model had been designed for minimizing privacy loss in the presence of untrusted service providers, so that providers can be prevented from disclosing information to third parties for secondary uses [30]. A conditional privacy-preserving authentication with access linkability (CPAL) for roaming service, to provide universal secure roaming service and multilevel privacy preservation [31].…”

Section: Privacy-preserving For Iotmentioning

confidence: 99%

Efficient location privacy algorithm for Internet of Things (IoT) services and applications

Sun

Chang

Ramachandran

et al. 2017

Journal of Network and Computer Applications

141

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Location-based Services (LBS) have become a very important area for research with the rapid development of Internet of Things (IoT) technology and the ubiquitous use of smartphones and social networks in our daily lives. Although users can enjoy a lot of flexibility and conveniences from the LBS with IoT, they may also lose their privacy. Untrusted or malicious LBS servers with all users' information can track users in various ways or release personal data to third parties. In this work, we first analyze the current dummy-location selection (DLS) algorithm-an efficient location privacy preservation approach and design an attack algorithm for DLS (ADLS) for test emerging IoT security. For efficiently preserving user's location privacy, we propose a novel dummy location privacy-preserving (DLP) algorithm by considering both computational costs and various privacy requirements of different users. Extensive simulation experiments have been carried out to evaluate the efficiency of the proposed schemes. Evaluation results show that the ADLS algorithm has a high probability of identifying the user's real location out from chosen dummy locations in the DLS algorithm. Our proposed DLP algorithm has clear advantages over the DLS algorithm in term of lower probability of revealing the user's real location and improved computational cost and efficiency (i.e., time, speed, accuracy, and complexity) while preserve the same privacy level as DLS algorithm.

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Efficient and privacy-preserving access to sensor data for Internet of Things (IoT) based services

Cited by 13 publications

References 21 publications

Internet of Things and data mining: From applications to techniques and systems

Internet of Things and data mining: From applications to techniques and systems

Using Smart Contract for Privacy Preserving in Internet of Things (IoT) Environments

Efficient location privacy algorithm for Internet of Things (IoT) services and applications

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