Secure Healthcare Data Aggregation and Transmission in IoT—A Survey

Ullah, Ata; Azeem, Muhammad; Ashraf, Humaira; Alaboudi, Abdulellah A.; Humayun, Mamoona; Jhanjhi, N. Z.

doi:10.1109/access.2021.3052850

Cited by 148 publications

(49 citation statements)

References 121 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Authors in [24] presented a comprehensive survey for the data collection schemes in healthcare. The study analyzed different data collection and secure transmission schemes to provide a suggested reliable and secured data transmission taxonomy with low computational cost and compression ratio.…”

Section: Related Reviews Studiesmentioning

confidence: 99%

The Internet of Things and Architectures of Big Data Analytics: Challenges of Intersection at Different Domains

2022

View full text Add to dashboard Cite

The current exponential advancements in the Internet of Things (IoT) technologies pave a vast intelligent computing platform by integrating smart objects with sensing, processing and communication capabilities. The core element of IoT is the complex big data generated from different interconnected sources at real-time, presenting divergent processing and analysis challenges. Best practices in software engineering have been continuously addressed in IoT technologies to handle such big data efficiently at different domains. Despite of the massive studies dedicated for IoT, no explicit processing architecture is proposed based on real investigation of software engineering concepts and big data analytics characteristics in IoT. This paper provides a systematic literature review for the current state-of-the-art of IoT systems in different domains. The study investigates the current techniques and technologies that serve IoT systems from the big data analytics and software engineering perspectives, revealing a matrix for the specific IoT data features and their encountered challenges and gaps for each domain. The review deduces a proposed domain-independent software architecture for big IoT data analytics, maintaining various IoT data processing challenges, including data scalability, timeliness, heterogeneity, inconsistency, confidentiality and correlations. Finally, the main research gaps are emphasized for future considerations.

show abstract

Section: Related Reviews Studiesmentioning

confidence: 99%

The Internet of Things and Architectures of Big Data Analytics: Challenges of Intersection at Different Domains

2022

View full text Add to dashboard Cite

show abstract

“…Hence, it is better to deploy blockchain mechanism there for the secure processing and storage of sensitive healthcare data. Here, AI can also play an important role in the prediction of different health-related phenomena, like chances of getting heart attack, diabetic shocks, and effective role of a medicine for a specific disease [23,34,35].…”

Section: Intelligent Transportationmentioning

confidence: 99%

Blockchain‐Envisioned Secure Authentication Approach in AIoT: Applications, Challenges, and Future Research

Wazid

Das

2021

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

The Artificial Intelligence of Things (AIoT) is the amalgamation of Artificial Intelligence (AI) methods and the Internet of Things (IoT) infrastructure, which are deployed there to improve the overall performance of the system. AIoT can be deployed to achieve more efficient IoT operations; thereby can improve human-machine interactions and provide better data analysis. AI methods can be used to transform IoT data into useful information for the better decision-making processes, and it further increases the overall usability of the system. AIoT frameworks are very useful and applicable in a variety of applications, like security and surveillance system, smart home, intelligent transportation system, smart farming, secure and safe healthcare monitoring, industrial automation and control, eCommerce, logistics operations and control, and many more. However, AIoT frameworks may have issues related to data security and privacy as they are vulnerable to various types of information security-related attacks. These issues further cause the serious consequences, like the unauthorized data leakage and data update. Blockchain is a specific type of database. It is a digital ledger of transactions, which is duplicated and distributed across the entire network of computer systems. It stores data in the form of some blocks, which are then chained together. Blockchain is tamper proof and provides more security as compared to the traditional security mechanisms. Hence, blockchain can be integrated in various AIoT applications to provide more security. A generalized blockchain-envisioned secure authentication framework for AIoT has been proposed. The adversary model of blockchain-envisioned secure authentication framework for AIoT is also highlighted that covers most of the potential threats of a kind of communication environment. Various applications of the proposed framework are also discussed. Furthermore, different issues and challenges of the proposed framework are highlighted. In the end, we also provide some future research directions relevant to the proposed framework.

show abstract

“…Prior studies in the field of healthcare in the IoT indicate the importance of using applications and the use of the IoT in the field of health since it has an important role in promoting and developing health services and benefits [20][21][22][23][24][25]. The structure of the Internet of things and the healthcare monitoring systems are described in this section.…”

Section: Wireless Communications and Mobile Computingmentioning

confidence: 99%

Presenting a Reliable Routing Approach in IoT Healthcare Using the Multiobjective‐Based Multiagent Approach

Javid

Mirzaei

2021

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

Developments in information and related technologies have led to a wider use of the Internet of things (IoT). By integrating both virtual and physical worlds, IoT creates an integrated communication framework of interrelated things and operating systems. With the advent of IoT systems based on digital remote care, transferring medical data is becoming a daily routine. Healthcare is one of the most popular IoT applications and tries to monitor patients’ vital signs during the day for weeks and to eliminate the need for hospitalization. In a healthcare system, many sensors are installed to collect the patient’s information, including environmental monitoring sensors and vital and unstructured message sensors in order to reduce the patients’ expenses. The IoT network contains flexible sensors in dynamically changing environments where sensors collect environmental information and send it to nursing stations for healthcare applications. Due to the wireless nature of IoT networks, secure data transmission in the healthcare context is very important. Data collected from sensors embedded in healthcare devices may be lost for various reasons along the transmission path. Therefore, establishing a secure communication path in IoT networks in the context of healthcare is of great importance. In this paper, in order to provide a reliable data transfer protocol in the context of healthcare, a reliable routing using multiobjective genetic algorithm (RRMOGA) method is presented. The contribution of this paper can be summarized in two steps: (i) using a multiobjective optimization approach to find near-optimal paths and (ii) using reliable agents in the network to find backup paths. The simulation outcomes reveal that the proposed approach, based on the use of the multiobjective optimization approach, tries to find optimal paths for information transfer that improve the main parameters of the network. Also, the use of secure agents leads to a secure information transfer in the network in the context of healthcare. Experimental results show that the proposed method has achieved reliability and data delivery rates, 99% and 99.9%, respectively. The proposed method has improved network lifetime, delivery rate, and delay by 14%, 2%, and 5.6%, respectively.

show abstract

Secure Healthcare Data Aggregation and Transmission in IoT—A Survey

Cited by 148 publications

References 121 publications

The Internet of Things and Architectures of Big Data Analytics: Challenges of Intersection at Different Domains

The Internet of Things and Architectures of Big Data Analytics: Challenges of Intersection at Different Domains

Blockchain‐Envisioned Secure Authentication Approach in AIoT: Applications, Challenges, and Future Research

Presenting a Reliable Routing Approach in IoT Healthcare Using the Multiobjective‐Based Multiagent Approach

Contact Info

Product

Resources

About