A Real-time Linked Dataspace for the Internet of Things: Enabling “Pay-As-You-Go” Data Management in Smart Environments

Curry, Edward; Derguech, Wassim; Hasan, Souleiman; Kouroupetroglou, Christos; Hassan, Umair ul

doi:10.1016/j.future.2018.07.019

Cited by 39 publications

(21 citation statements)

References 38 publications

(55 reference statements)

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“…The smartphones, wearables, smartwatches with embedded sensors are examples of smart IoT devices. For data collection, these devices are deployed in an unrestrained environment [28]. These devices are held by the subjects while performing a different set of activities.…”

Section: A Iot Data Acquisitionmentioning

confidence: 99%

Authentication of Remote IoT Users Based on Deeper Gait Analysis of Sensor Data

et al. 2020

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In IoT based systems, authentication of users and devices is a major challenge where the traditional authentication mechanisms such as login-password are no longer supportable. It requires continuous authentication methods to ensure authenticity of the users and devices specifically for long sessions. The authentication through the IoT-Sensors based data has already gained the attention of a considerable number of researchers as it does not require direct involvement of the users and provide an extra layer of security and user privacy. Due to the instability of IoT-Sensor data, the authentication techniques need to extract a large number of features to produce high-accurate results. Moreover, the limited capabilities of computation, communication, storage, and the small battery power of IoT devices further makes its implementation hard. In this paper, we have introduced a user authentication framework for remote IoT users based on unique walking patterns to extract gait-related features with minimum data samples and cycle length. For an in-depth analysis of the distinctive features of the sensor-based gait profiles, we have applied an ECG signal processing technique. The proposed approach applies to a diverse range of IoT devices such as cellphones, smartwatches, and wearable sensors. The main contribution of the proposed approach is the deeper gait analysis with the least number of features and data for authentication purposes. We have introduced an authentication algorithm for feature comparison. The machine learning models have been applied to the gait based profiles for validation of the proposed approach. The detailed experimental analysis of different data sets has achieved an accuracy of 94% and an equal error rate (EER) of 6% higher than the existing approaches.

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Section: A Iot Data Acquisitionmentioning

confidence: 99%

Authentication of Remote IoT Users Based on Deeper Gait Analysis of Sensor Data

et al. 2020

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“…Curry et al [7] specifically focus on a real-time linked dataspaces for Internet of Things enabled smart environments. They highlight how the use of linked dataspaces can enable analytics and decision support applications.…”

Section: Papersmentioning

confidence: 99%

Special Issue: Big Data for context-aware applications and intelligent environments

Preuveneers

Ilie‐Zudor

2019

Future Generation Computer Systems

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Disruptive paradigm shifts such as the Internet of Things (IoT) and Cyber-Physical Systems (CPS) are creating a wealth of streaming context information. Large-scale context-awareness combining IoT and Big Data drive the creation of smarter application ecosystems in diverse vertical domains, including smart health, finance, smart grids and cities, transportation, Industry 4.0, etc. This special issue addresses core topics on the design, the use and the evaluation of Big Data enabling technologies to build next-generation context-aware applications and computing systems for future intelligent environments.

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“…From the beginning of the current decade, ontologies that represent the knowledge from different energy domains have been developed. These ontologies support energy management applications focused on improving the current grid sustainability to make the Smart Grid vision a reality [11]. These applications can be classified into different types according to the Smart Grid scenario/infrastructure where they are deployed, i.e., Smart Home or building energy management applications.…”

Section: Motivational Scenariomentioning

confidence: 99%

Experiences on applying SPL Engineering Techniques to Design a (Re) usable Ontology in the Energy Domain

Cuenca

Larrinaga

Curry

2019

International Conferences on Software Engineering and Knowledge Engineering

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Global ontologies must provide a balance of reusabilityusability to minimize the ontology reuse effort in different applications. To achieve this balance, ontology design methods focus on designing layered ontologies that classify into abstraction layers the common domain knowledge (reused by most applications) and the variant domain knowledge (reused by specific application types). This classification is performed from scratch by domain experts and ontology engineers. Hence, the design of reusable and usable ontologies that represent complex domains takes a lot of effort. Considering how common and variant software features are classified when designing Software Product Lines (SPLs), we argue that SPL engineering techniques can facilitate the domain knowledge classification taking as reference existing ontologies. In this paper, we show the experiences of applying SPL and ontology design techniques in combination to design a reusable and usable global ontology for the energy domain. Domain experts and ontology engineers evaluated the proposed method. The results show that SPL engineering techniques enable a systematic and accurate domain knowledge classification, thus saving ontology design effort.

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A Real-time Linked Dataspace for the Internet of Things: Enabling “Pay-As-You-Go” Data Management in Smart Environments

Cited by 39 publications

References 38 publications

Authentication of Remote IoT Users Based on Deeper Gait Analysis of Sensor Data

Authentication of Remote IoT Users Based on Deeper Gait Analysis of Sensor Data

Special Issue: Big Data for context-aware applications and intelligent environments

Experiences on applying SPL Engineering Techniques to Design a (Re) usable Ontology in the Energy Domain

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