IoT security: Review, blockchain solutions, and open challenges

Internet of Things security

Buildings are among the largest consumers of electricity in the US. A significant portion of this energy use in buildings can be attributed to HVAC systems used to maintain comfort for occupants. In most cases these building HVAC systems run on fixed schedules and do not employ any fine grained control based on detailed occupancy information. In this paper we present the design and implementation of a presence sensor platform that can be used for accurate occupancy detection at the level of individual offices. Our presence sensor is low-cost, wireless, and incrementally deployable within existing buildings. Using a pilot deployment of our system across ten offices over a two week period we identify significant opportunities for energy savings due to periods of vacancy. Our energy measurements show that our presence node has an estimated battery lifetime of over five years, while detecting occupancy accurately. Furthermore, using a building simulation framework and the occupancy information from our testbed, we show potential energy savings from 10% to 15% using our system.

[ACM Press the 2nd ACM Workshop - Zurich, Switzerland (2010.11.02-2010.11.02)] Proceedings of the 2nd ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Building - BuildSys \'10 - Occupancy-driven energy management for smart building automation

Efficient IoT-based sensor BIG Data collection–processing and analysis in smart buildings

https://hal.archives-ouvertes.fr/hal-01780365/document

Internet of things security: A top-down survey

This paper presents the main foundations of big data applied to smart cities. A general Internet of Things based architecture is proposed to be applied to different smart cities applications. We describe two scenarios of big data analysis. One of them illustrates some services implemented in the smart campus of the University of Murcia. The second one is focused on a tram service scenario, where thousands of transit-card transactions should be processed. Results obtained from both scenarios show the potential of the applicability of this kind of techniques to provide profitable services of smart cities, such as the management of the energy consumption and comfort in smart buildings, and the detection of travel profiles in smart transport.

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Applicability of Big Data Techniques to Smart Cities Deployments

The strong development of the Internet of Things (IoT) is dramatically changing traditional perceptions of the current Internet towards an integrated vision of smart objects interacting with each other. While in recent years many technological challenges have already been solved through the extension and adaptation of wireless technologies, security and privacy still remain as the main barriers for the IoT deployment on a broad scale. In this emerging paradigm, typical scenarios manage particularly sensitive data, and any leakage of information could severely damage the privacy of users. This paper provides a concise description of some of the major challenges related to these areas that still need to be overcome in the coming years for a full acceptance of all IoT stakeholders involved. In addition, we propose a distributed capability-based access control mechanism which is built on public key cryptography in order to cope with some of these challenges. Specifically, our solution is based on the design of a lightweight token used for access to CoAP Resources, and an optimized implementation of the Elliptic Curve Digital Signature Algorithm (ECDSA) inside the smart object. The results obtained from our experiments demonstrate the feasibility of the proposal and show promising in order to cover more complex scenarios in the future, as well as its application in specific IoT use cases.

A decentralized approach for security and privacy challenges in the Internet of Things

Nowadays, buildings are increasingly expected to meet higher and more complex performance requirements. Among these requirements, energy efficiency is recognized as an international goal to promote energy sustainability of the planet. Different approaches have been adopted to address this goal, the most recent relating consumption patterns with human occupancy. In this work, we analyze what are the main parameters that should be considered to be included in any building energy management. The goal of this analysis is to help designers to select the most relevant parameters to control the energy consumption of buildings according to their context, selecting them as input data of the management system. Following this approach, we select three reference smart buildings with different contexts, and where our automation platform for energy monitoring is deployed. We carry out some experiments in these buildings to demonstrate the influence of the parameters identified as relevant in the energy consumption of the buildings. Then, in two of these buildings are applied different control strategies to save electrical energy. We describe the experiments performed and analyze the results. The first stages of this evaluation have already resulted in energy savings of about 23% in a real scenario.

/pdf/how-can-we-tackle-energy-efficiency-in-iot-basedsmart-54yvlg2m2b.pdf

How can We Tackle Energy Efficiency in IoT BasedSmart Buildings

SAFIR: Secure access framework for IoT-enabled services on smart buildings

Due to the high impact that energy consumption by buildings has at global scale, energy-efficient buildings to reduce $$\mathrm{CO}_2$$CO2 emissions and energy consumption are needed. In this work we present a novel approach to energy saving in buildings through the identification of the relevant parameters and the application of Soft Computing techniques to generate predictive models of energy consumption in buildings. Using such models it is possible to define strategies for optimizing the day-to-day energy consumption of buildings. To verify the feasibility of this proposal, we apply our approach to a reference building for which we have contextual data from a complete year of monitoring. First, we characterize the building in terms of its contextual features and energy consumption, and then select the most appropriate techniques to generate the most accurate model of our reference building charged with estimating the energy consumption, given a concrete set of inputs. Finally, considering the energy usage profile of the building, we propose specific control actions and strategies to save energy.

/pdf/big-data-the-key-to-energy-efficiency-in-smart-buildings-3tn4etu7jy.pdf

M. Victoria Moreno

Papers

Applicability of Big Data Techniques to Smart Cities Deployments

A decentralized approach for security and privacy challenges in the Internet of Things

How can We Tackle Energy Efficiency in IoT BasedSmart Buildings

SAFIR: Secure access framework for IoT-enabled services on smart buildings

Big data: the key to energy efficiency in smart buildings