PAgIoT – Privacy-preserving Aggregation protocol for Internet of Things

González-Manzano, Lorena; Fuentes, José María de; Pastrana, Sergio; Peris-López, Pedro; Encinas, Luis Hernández

doi:10.1016/j.jnca.2016.06.001

Cited by 31 publications

(11 citation statements)

References 43 publications

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“…They introduced the Dummy Location Privacy-Preserving (DLP) algorithm which chooses the optimal dummy locations to prevent the attacker from extracting real users’ locations. Finally, Gonzalez-Manzano et al [16] designed PagIoT, a privacy-preserving aggregation protocol that contributes to the aggregation of data and the correlation between the values. However, the aforementioned protocols have not been tested to real-world operational environments that differ greatly from simulation environments and strong limitations have been assumed to evaluate these.…”

Section: Related Workmentioning

confidence: 99%

Location Privacy Protection in Distributed IoT Environments Based on Dynamic Sensor Node Clustering

Dimitriou

Roussaki

2019

Sensors

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One of the most significant challenges in Internet of Things (IoT) environments is the protection of privacy. Failing to guarantee the privacy of sensitive data collected and shared over IoT infrastructures is a critical barrier that delays the wide penetration of IoT technologies in several user-centric application domains. Location information is the most common dynamic information monitored and lies among the most sensitive ones from a privacy perspective. This article introduces a novel mechanism that aims to protect the privacy of location information across Data Centric Sensor Networks (DCSNs) that monitor the location of mobile objects in IoT systems. The respective data dissemination protocols proposed enhance the security of DCSNs rendering them less vulnerable to intruders interested in obtaining the location information monitored. In this respect, a dynamic clustering algorithm is that clusters the DCSN nodes not only based on the network topology, but also considering the current location of the objects monitored. The proposed techniques do not focus on the prevention of attacks, but on enhancing the privacy of sensitive location information once IoT nodes have been compromised. They have been extensively assessed via series of experiments conducted over the IoT infrastructure of FIT IoT-LAB and the respective evaluation results indicate that the dynamic clustering algorithm proposed significantly outperforms existing solutions focusing on enhancing the privacy of location information in IoT.

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Section: Related Workmentioning

confidence: 99%

Location Privacy Protection in Distributed IoT Environments Based on Dynamic Sensor Node Clustering

Dimitriou

Roussaki

2019

Sensors

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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%

“…Henze, et al presented an user-driven privacy enforcement appraoch for cloud-based services in the IoT, which focuses on privacy preserving for individual end-users [28]. 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].…”

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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“…PAgIoT is proposed, which is a privacy-preserving aggregation protocol. 9 In PAgIoT, data are decomposed into a set of attributes which are aggregated separately. A central node (sink) queries for the value of certain attributes, and remainder nodes respond depending on whether they possess or not these attributes.…”

Section: Related Workmentioning

confidence: 99%

A privacy protection mechanism for numerical control information in Internet of things

2017

International Journal of Distributed Sensor Networks

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The application of numerical control machine tool in the Internet of things has attracted large number of attention. It is a complex network system that integrates sensor network, Internet, and mobile communication network. However, some security issues have not been solved by Internet security technology. In order to enhance the security of system, we, respectively, propose a lightweight authentication method for wireless sensor networks and an Internet data privacy protection strategy based on organizational characteristics of computerized numerical control machine tool and the numerical control information transmission mode in Internet of things. The two methods constitute a privacy protection mechanism for numerical control information in Internet of things. In order to show the effectiveness of the privacy protection mechanisms, series of analysis about safety is presented. Analysis results show that this mechanism can ensure the security of information and the privacy of the numerical control machine tool in Internet of things.

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PAgIoT – Privacy-preserving Aggregation protocol for Internet of Things

Cited by 31 publications

References 43 publications

Location Privacy Protection in Distributed IoT Environments Based on Dynamic Sensor Node Clustering

Location Privacy Protection in Distributed IoT Environments Based on Dynamic Sensor Node Clustering

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

A privacy protection mechanism for numerical control information in Internet of things

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