Cloud-Based Data Analytics: Applications, Security Issues, and Challenges

Senapaty, Murali Krishna; Mishra, Gayatri; Ray, Abhishek

doi:10.1201/9781003048367-36

Cited by 2 publications

(2 citation statements)

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“…Cloud-based architectures are convenient for managing the vast amount of data that can be generated by wireless sensors without overwhelming local computer systems [23,24]. Still, the use of external public services raises a two-level issue regarding the privacy of the patient: (i) The monitoring platform must comply with the regulatory framework on sensitive data, e.g., the European GDPR [25], and (ii) technical solutions must be adopted to ensure secure access to the data without involving the cloud service, which, in general, could be an honest-but-curious or even malevolent actor.…”

Section: Introductionmentioning

confidence: 99%

Privacy-Aware Architectures for NFC and RFID Sensors in Healthcare Applications

Raso

Bianco

Bracciale

et al. 2022

Sensors

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World population and life expectancy have increased steadily in recent years, raising issues regarding access to medical treatments and related expenses. Through last-generation medical sensors, NFC (Near Field Communication) and radio frequency identification (RFID) technologies can enable healthcare internet of things (H-IoT) systems to improve the quality of care while reducing costs. Moreover, the adoption of point-of-care (PoC) testing, performed whenever care is needed to return prompt feedback to the patient, can generate great synergy with NFC/RFID H-IoT systems. However, medical data are extremely sensitive and require careful management and storage to protect patients from malicious actors, so secure system architectures must be conceived for real scenarios. Existing studies do not analyze the security of raw data from the radiofrequency link to cloud-based sharing. Therefore, two novel cloud-based system architectures for data collected from NFC/RFID medical sensors are proposed in this paper. Privacy during data collection is ensured using a set of classical countermeasures selected based on the scientific literature. Then, data can be shared with the medical team using one of two architectures: in the first one, the medical system manages all data accesses, whereas in the second one, the patient defines the access policies. Comprehensive analysis of the H-IoT system can be useful for fostering research on the security of wearable wireless sensors. Moreover, the proposed architectures can be implemented for deploying and testing NFC/RFID-based healthcare applications, such as, for instance, domestic PoCs.

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Section: Introductionmentioning

confidence: 99%

Privacy-Aware Architectures for NFC and RFID Sensors in Healthcare Applications

Raso

Bianco

Bracciale

et al. 2022

Sensors

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“…The term "edge analytics" refers to the collecting and analysis of data that takes place at or near a device's edge. Cloud-based analytics [3] are then performed on this data. In contrast to edge analytics, edge intelligence uses Artificial Intelligence to conduct operations directly at the edge of the network.…”

Section: Introductionmentioning

confidence: 99%

Definition and Applications of SDN, NFV, Edge Computing and AI/ML Techniques

Capra

2022

JMC

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A surge in Artificial Intelligence (AI) services and applications has been spurred by advances in deep learning. Massive data generation at the network edge is being sparked by the fast advancements in mobile computing and Artificial Intelligence of Things (AIoT). Big data can only be completely realized if the AI frontiers are pushed to the network edge, propelled by the successes of AI and IoT. It is hoped that Edge Computing would help to fulfil this trend by supporting AI applications that are computationally heavy on edge devices. Machine learning algorithms may be deployed to the end devices in which the data is created thanks to Edge AI. For every individual and business, Edge Intelligence has the ability to give AI at any moment, any place. This paper is limited to evaluating the definitions, history and applications of Software Defined Networks (SDNs), Network Functions Virtualization (NFV), Edge Computing (EC), Artificial Intelligence (AI)/Machine Learning (ML) techniques.

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Cloud-Based Data Analytics: Applications, Security Issues, and Challenges

Cited by 2 publications

References 0 publications

Privacy-Aware Architectures for NFC and RFID Sensors in Healthcare Applications

Privacy-Aware Architectures for NFC and RFID Sensors in Healthcare Applications

Definition and Applications of SDN, NFV, Edge Computing and AI/ML Techniques

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