Privacy of the Internet of Things: A Systematic Literature Review

The Internet of Things’ potential for major privacy invasion is a concern. This paper reports on a systematic literature review of privacy-preserving solutions appearing in the research literature and in the media. We analysed proposed solutions in terms of the techniques they deployed and the extent to which they satisfied core privacy principles. We found that very few solutions satisfied all core privacy principles. We also identified a number of key knowledge gaps in the course of the analysis. In particular, we found that most solution providers assumed that end users would be willing to expend effort to preserve their privacy; that they would be motivated to take action to ensure that their privacy was respected. The validity of this assumption needs to be proved, since it cannot simply be assumed that people would necessarily be willing to engage with privacy-preserving solutions. We suggest this as a topic for future research

A Study on Sanctuary and Seclusion Issues in Internet-of-Things

Internet-of-Things (IoT) are everywhere in our daily life. They are used in our homes, in hospitals, deployed outside to control and report the changes in environment, prevent fires, and many more beneficial functionality. However, all those benefits can come of huge risks of seclusion loss and sanctuary issues. To secure the IoT devices, many research works have been con-ducted to countermeasure those problems and find a better way to eliminate those risks, or at least minimize their effects on the user�s seclusion and sanctuary requirements. The study consists of four segments. The first segment will explore the most relevant limitations of IoT devices and their solutions. The second one will present the classification of IoT attacks. The next segment will focus on the mechanisms and architectures for authentication and access control. The last segment will analyze the sanctuary issues in different layers

TAW: cost-effective threshold authentication with weights for internet of things

In the Internet of Things, based on the collaboration of sensing nodes, sensing data are collected and transmitted. The collaboration of sensing nodes also plays an important role in the safeguard of the Internet of Things. Owing to the limited ability of the single sensing node, the threshold authentication based on the collaboration of sensing nodes can improve the trust of security authentication of sensing nodes. The current threshold authentication schemes may require high-computational complexity, and more importantly, most of them are instantiated by membership authentication. It’s challenging to apply the current state of the arts to the case where sensing nodes with various weights join together to fulfill a relatively lightweight authentication. In this paper, we first design a communication key distribution scheme for sensing networks based on a symmetric operator. Using the permutation function, the scheme is able to generate characteristic sequences to improve the efficiency of key distribution in sensing networks. In addition, we propose a threshold authentication scheme based on weights, in which the higher weight represents the more important role in authentication. Our authentication scheme only requires lightweight operations, so that, it is extremely friendly to the IoT nodes with restricted computation power. The security analysis and the case verification demonstrate that our novel authentication protects IoT nodes without yielding significantly computational burden to the nodes

A Survey on Smartphone-Based Crowdsensing Solutions

© 2016 Willian Zamora et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.[EN] In recent years, the widespread adoption of mobile phones, combined with the ever-increasing number of sensors that smartphones are equipped with, greatly simplified the generalized adoption of crowdsensing solutions by reducing hardware requirements and costs to a minimum. These factors have led to an outstanding growth of crowdsensing proposals from both academia and industry. In this paper, we provide a survey of smartphone-based crowdsensing solutions that have emerged in the past few years, focusing on 64 works published in top-ranked journals and conferences. To properly analyze these previous works, we first define a reference framework based on how we classify the different proposals under study. The results of our survey evidence that there is still much heterogeneity in terms of technologies adopted and deployment approaches, although modular designs at both client and server elements seem to be dominant. Also, the preferred client platform is Android, while server platforms are typically web-based, and client-server communications mostly rely on XML or JSON over HTTP. The main detected pitfall concerns the performance evaluation of the different proposals, which typically fail to make a scalability analysis despite being critical issue when targeting very large communities of users.This work was partially supported by the Ministerio de Economia y Competitividad, Programa Estatal de Investigacion, Desarrollo e Innovacion Orientada a los Retos de la Sociedad, Proyectos I+D+I 2014, Spain, under Grant TEC2014-52690-R, the "Universidad Laica Eloy Alfaro de Manabi-ULEAM," and the "Programa de Becas SENESCYT de la Republica del Ecuador."Zamora-Mero, WJ.; Tavares De Araujo Cesariny Calafate, CM.; Cano Escribá, JC.; Manzoni, P. (2016). A Survey on Smartphone-Based Crowdsensing Solutions. Mobile Information Systems. 2016:1-26. https://doi.org/10.1155/2016/9681842S126201

Optimising data diffusion while reducing local resources consumption in Opportunistic Mobile Crowdsensing

[EN] The combination of Mobile Crowdsensing (MCS) with Opportunistic Networking (Opp-Net) allows mobile users to share sensed data easily and conveniently without the use of fixed infrastructure. OppNet is based on intermittent connectivity among wireless mobile devices, in which mobile nodes may store, carry and forward messages (sensing information) by taking advantage of wireless ad hoc communication opportunities. A common approach for the diffusion of this sensing data in OppNet is the epidemic protocol, which carries out a fast data diffusion at the expense of increasing the usage of local buffers on mobile nodes and also the number of transmissions, thereby limiting scalability. A way to reduce this consumption of local resources is to set a message expiration time that forces the removal of old messages from local buffers. Since dropping messages too early may reduce the speed of information diffusion, we propose a dynamic expiration time setting to limit this effect. Moreover, we introduce an epidemic diffusion model for evaluating the impact of the expiration time. This model allows us to obtain optimal expiration times that achieve performances similar to those other approaches where no expiration is considered, with a significant reduction of local buffer and network usage. Furthermore, in our proposed model, the buffer utilisation remains steady with the number of nodes, whereas in other approaches it increases sharply. Finally, our approach is evaluated and validated in a mobile crowdsensing scenario, where students collect and broadcast information regarding a university campus, showing a significant reduction on buffer usage and nodes message transmissions, and therefore, decreasing battery consumption.This work was partially supported by the Ministerio de Ciencia, Innovación y Universidades, Spain, under Grant RTI2018- 096384-B-I00. 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