Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Tracing Your Smart-Home Devices Conversations: A Real World IoT Traffic Data-Set

View through CrossRef
Smart-home installations exponential growth has raised major security concerns. To this direction, the GHOST project, a European Union Horizon 2020 Research and Innovation funded project, aims to develop a reference architecture for securing smart-homes IoT ecosystem. It is required to have automated and user friendly security mechanisms embedded into smart-home environments, to protect the users’ digital well being. GHOST project aims to fulfill this requirement and one of its main functionalities is the traffic monitoring for all IoT related network protocols. In this paper, the traffic capturing and monitoring mechanism of the GHOST system, called NDFA, is presented, as the first mechanism that is able to monitor smart-home activity in a holistic way. With the help of the NDFA, we compile the GHOST-IoT-data-set, an IoT network traffic data-set, captured in a real world smart-home installation. This data-set contains traffic from multiple network interfaces with both normal real life activity and simulated abnormal functioning of the devices. The GHOST-IoT-data-set is offered to the research community as a proof of concept to demonstrate the ability of the NDFA module to process the raw network traffic from a real world smart-home installation with multiple network interfaces and IoT devices.
Title: Tracing Your Smart-Home Devices Conversations: A Real World IoT Traffic Data-Set
Description:
Smart-home installations exponential growth has raised major security concerns.
To this direction, the GHOST project, a European Union Horizon 2020 Research and Innovation funded project, aims to develop a reference architecture for securing smart-homes IoT ecosystem.
It is required to have automated and user friendly security mechanisms embedded into smart-home environments, to protect the users’ digital well being.
GHOST project aims to fulfill this requirement and one of its main functionalities is the traffic monitoring for all IoT related network protocols.
In this paper, the traffic capturing and monitoring mechanism of the GHOST system, called NDFA, is presented, as the first mechanism that is able to monitor smart-home activity in a holistic way.
With the help of the NDFA, we compile the GHOST-IoT-data-set, an IoT network traffic data-set, captured in a real world smart-home installation.
This data-set contains traffic from multiple network interfaces with both normal real life activity and simulated abnormal functioning of the devices.
The GHOST-IoT-data-set is offered to the research community as a proof of concept to demonstrate the ability of the NDFA module to process the raw network traffic from a real world smart-home installation with multiple network interfaces and IoT devices.

Related Results

Prostor doma u hrvatskim igranim filmovima s temom domovinskog rata
Prostor doma u hrvatskim igranim filmovima s temom domovinskog rata
The dissertation explores the formation of domestic space in contemporary Croatian society through its presentations in the medium of feature films. The cinematic domestic spaces a...
On Privacy and Security in Smart Connected Homes
On Privacy and Security in Smart Connected Homes
The growth and presence of heterogeneous sensor-equipped Internet-connected devices inside the home can increase efficiency and quality of life for the residents. Simultaneously, t...
On Privacy and Security in Smart Connected Homes
On Privacy and Security in Smart Connected Homes
The growth and presence of heterogeneous sensor-equipped Internet-connected devices inside the home can increase efficiency and quality of life for the residents. Simultaneously, t...
Everyday Life in the "Tourist Zone"
Everyday Life in the "Tourist Zone"
This article makes a case for the everyday while on tour and argues that the ability to continue with everyday routines and social relationships, while at the same time moving thro...
TYPES OF AI ALGORİTHMS USED İN TRAFFİC FLOW PREDİCTİON
TYPES OF AI ALGORİTHMS USED İN TRAFFİC FLOW PREDİCTİON
The increasing complexity of urban transportation systems and the growing volume of vehicles have made traffic congestion a persistent challenge in modern cities. Efficient traffic...
Deception-Based Security Framework for IoT: An Empirical Study
Deception-Based Security Framework for IoT: An Empirical Study
<p><b>A large number of Internet of Things (IoT) devices in use has provided a vast attack surface. The security in IoT devices is a significant challenge considering c...
Traffic Prediction in 5G Networks Using Machine Learning
Traffic Prediction in 5G Networks Using Machine Learning
The advent of 5G technology promises a paradigm shift in the realm of telecommunications, offering unprecedented speeds and connectivity. However, the ...
Modeling of Trusted Public Emergency Services for Smart Cities Using Blockchain and IoT-based Cognitive Networks
Modeling of Trusted Public Emergency Services for Smart Cities Using Blockchain and IoT-based Cognitive Networks
Abstract The Internet of Things (IoT) recently gained attention from the last few years due to various smart city applications deployment. The existing literature discusses...

Back to Top