MQTT-G: A Publish/Subscribe Protocol with Geolocation

Bryce, Robert; Shaw, Thomas Shuler; Srivastava, Gautam

doi:10.1109/tsp.2018.8441479

Cited by 34 publications

(24 citation statements)

References 10 publications

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“…It is worth noting here that the constraint of interference becomes a form of summation of simple variables. Thus, the SPI encryption method of interference quantization can be introduced to simplify the original data encryption interference problem [21][22][23][24][25][26].…”

Section: Security Encryption Methods Of Upimentioning

confidence: 99%

An Efficient Encryption Algorithm for the Security of Sensitive Private Information in Cyber-Physical Systems

2019

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The new developments in smart cyber-physical systems can be shown to include smart cities, Internet of things (IoT), and for the most part smart anything. To improve the security of sensitive personal information (SPI) in cyber-physical systems, we present some novel ideas related to the encryption of SPI. Currently, there are issues in traditional encryption methods, such as low speed of information acquisition, low recognition rate, low utilization rate of effective information resources, and high delay of information query. To address these issues, we propose a novel efficient encryption algorithm for the security of incremental SPI. First, our proposed method analyzes user information resources and determines valid data to be encrypted. Next, it uses adaptive acquisition methods to collect information, and uses our encryption method to complete secure encryption of SPI according to the acquisition results. Our experimental analysis clearly shows that the algorithm effectively improves the speed of information acquisition as well as effective information recognition rate, thus enhancing the security of SPI. The encryption model in turn can provide a strong guarantee for user information security.

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Section: Security Encryption Methods Of Upimentioning

confidence: 99%

An Efficient Encryption Algorithm for the Security of Sensitive Private Information in Cyber-Physical Systems

2019

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“…Consumer Producer Consumer Producer [11] Yes No No Yes [12,13] No Yes Yes No [21] No Yes Yes No [22] No Yes Yes No [23] No Yes Yes No [24] No Yes Yes Partially [9,10] Partially Partially Yes Yes [4] Partially Partially Yes Yes [14,25] Yes Yes Yes Yes Chen et al [11] propose a spatial middleware service that delivers messages to clients when they enter "zones" defined by data producers, i.e., producer geofences. While this allows data producers to control data distribution based on areas they consider as relevant, data consumers cannot control data distribution with consumer geofences.…”

Section: Rwmentioning

confidence: 99%

“…The authors of [12,13,21,22,23] consider the consumer geofence and the producer location, i.e., the geo-context dimensions needed for the consumer GeoCheck. However, neither group of authors lets data producers control the matching of messages based on producer geofences and consumer locations (producer GeoCheck).…”

Section: Rwmentioning

confidence: 99%

GeoBroker: Leveraging geo-contexts for IoT data distribution

Hasenburg

Bermbach

2020

Computer Communications

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In the Internet of Things, the relevance of data often depends on the geographic context of data producers and consumers. Today's data distribution services, however, mostly focus on data content and not on geo-context, which could help to reduce the dissemination of excess data in many IoT scenarios. In this paper, we propose to use the geo-context information associated with devices to control data distribution. We define what geocontext dimensions exist and compare our definition with concepts from related work.Furthermore, we designed GeoBroker, a data distribution service that uses the location of things, as well as geofences for messages and subscriptions, to control data distribution. This way, we enable new IoT application scenarios while also increasing overall system efficiency for scenarios where geo-contexts matter by delivering only relevant messages. We evaluate our approach based on a proof-of-concept prototype and several experiments.

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“…Previous to the work here, we had attempted to tackle MQTTg using the Mosquitto implementation [7,8] of the protocol. Mosquitto is an open source implementation of MQTT 3.1.1 which was prescribed recently in [12].…”

Section: Introductionmentioning

confidence: 99%

Green Communication Protocol with Geolocation

Srivastava

Fisher

Bryce

et al. 2019

2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring)

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Green communications is the practice of selecting energy efficient communications, networking technologies and products. This process is followed by minimizing resource use whenever possible in all branches of communications. In this day and age, green communication is vital to the footprint we leave on this planet as we move into a completely digital age. One such communication tool is Message Queue Transport Telemetry or MQTT which is an open source publisher/subscriber standard for M2M (Machine to Machine) communication. It is well known for its low energy and bandwidth footprint and thus makes it highly suitable for Green Internet of Things (IoT) messaging situations where power usage is at a premium or in mobile devices such as phones, embedded computers or microcontrollers. It is a perfect tool for the green communication age upon us and more specifically Green IoT. One problem however with the original MQTT protocol is that it is lacking the ability to broadcast geolocation. In today's age of IoT however, it has become more pertinent to have geolocation as part of the protocol. In this paper, we add geolocation to the MQTT protocol and offer a revised version, which we call MQTTg. We describe the protocol here and show where we are able to embed geolocation successfully. We also offer a glimpse into an Android OS application we are developing for Open Source use.

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MQTT-G: A Publish/Subscribe Protocol with Geolocation

Cited by 34 publications

References 10 publications

An Efficient Encryption Algorithm for the Security of Sensitive Private Information in Cyber-Physical Systems

An Efficient Encryption Algorithm for the Security of Sensitive Private Information in Cyber-Physical Systems

GeoBroker: Leveraging geo-contexts for IoT data distribution

Green Communication Protocol with Geolocation

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