Big Data Analytics for Large Scale Wireless Body Area Networks; Challenges, and Applications

Abdulshaheed, Haider Rasheed; Abbas, Haider Hadi; Ahmed, Ehsan Qahtan; Al_Barazanchi, Israa

doi:10.1007/978-3-030-98741-1_35

Cited by 11 publications

(8 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The main goal of LOA is to achieve good class mean separation while maintaining limited variance around these means in the projection direction. Like PCA, LDA uses a linear combination of initial data to generate its features [24][25][26][27][28][29][30][31][32][33][34][35][36].…”

Section: Proposed Methodologymentioning

confidence: 99%

A Deep learning approach for trust-untrust nodes classification problem in WBAN

Mehdy¹,

Qasim²,

A.Habeeb³

et al. 2023

PEN

View full text Add to dashboard Cite

The enormous growth in demand for WBAN services has resulted in a new set of security challenges. The capabilities of WBAN are developing to meet these needs. The complexity, heterogeneity, and instability of the mobile context make it difficult to complete these duties successfully. A more secure and flexible WBAN setting can be attained using a trust-untrust nodes classification, which is one method to satisfy the security needs of the WBAN. Considering this, we present a novel Deep Learning (DL) approach for classifying WBAN nodes using spatial attention based iterative DBN (SA-IDBN). Z-score normalization is used to remove repetitive entries from the input data. Then, Linear Discriminate Analysis (LDA) is employed to retrieve the features from the normalized data. In terms of accuracy, latency, recall, and f-measure, the suggested method's performance is examined and contrasted with some other current approaches. Regarding the classification of WBAN nodes, the results are more favorable for the suggested method than for the ones already in use.

show abstract

Section: Proposed Methodologymentioning

confidence: 99%

A Deep learning approach for trust-untrust nodes classification problem in WBAN

Mehdy¹,

Qasim²,

A.Habeeb³

et al. 2023

PEN

View full text Add to dashboard Cite

show abstract

“…Notice that the DH technique is only used for key exchange, not for message encryption or decryption. If the doctor and patient want to communicate, they must first agree on a common key established using the DH method, which they may then use for encryption or decryption by lightweight encryption [20]- [25]. Figure 3 illustrates the Diffie Hellman key exchange algorithm for the Internet of Health Things (IoHT).…”

Section: Diffie Hellman Methodsmentioning

confidence: 99%

A secure telemedicine electronic platform based on lightweight cryptographic approach

2022

Self Cite

View full text Add to dashboard Cite

Telemedicine platforms have emerged as one of the most harnessed studies in recent years, especially after the spread of pandemics. Due to the epidemic, telemedicine distribution to rural or isolated areas has become an urgent need. However, there are several obstacles to providing remote medical care, the most significant of which is protecting patient data while sustaining the speed of communication between the patient and the medical staff. The significant of this study is to provides a lightweight encryption/decryption technique that uses on the internet of medical things in stance of bio-sensors and bio-actuators. This study is one of the cybersecurity approaches, such type of encryption has little effect on the speed of data transmission. The Diffie Hellman technique is used as a lightweight encryption method because it includes four encryption-keys. The efficiency of the proposed encryption method has been compared with several equivalent methods. According to experimental results, the proposed encryption method represents a lightweight and secure method which can accomplish the level of protection that required to secure medical information despite the data's disarray.

show abstract

“…e counting of neighbours in node's transmitting radius R c is denoted in equation (1). In the M × M field region, "M" is the value Ntk-Dimension, and the distance between ith neighbouring nodes is represented by dist 2 i .…”

Section: Cluster-head Selection Using Fuzzy Logicmentioning

confidence: 99%

“…The ongoing COVID-19 endemic, poor lifestyle choices, insufficient stress relief, rising healthcare costs, and an aging population all posed significant challenges to governments and healthcare organizations around the world. The growing number of patients has necessitated the use of advanced technologies to enable doctors to remotely monitor patients via wireless body area network (WBAN) sensors [ 1 ]. However, because WBAN networks involve remote access and sensitive and critical data, they necessitate extremely high levels of security and privacy during storage and processing.…”

Section: Introductionmentioning

confidence: 99%

Remote Monitoring of COVID-19 Patients Using Multisensor Body Area Network Innovative System

Al_Barazanchi

Hashim

Alkahtani

et al. 2022

Computational Intelligence and Neuroscience

Self Cite

View full text Add to dashboard Cite

As of late 2019, the COVID19 pandemic has been causing huge concern around the world. Such a pandemic posed serious threats to public safety, the well-being of healthcare workers, and the overall health of the population. If automation can be implemented in healthcare systems, patients could be better cared for and health industries could be less burdened. To combat such challenges, e-health requires apps and intelligent systems. Using WBAN sensors and networks, a doctor or medical professional can advise patients on the best course of action. Patients' fitness could be assessed using WBAN sensors without interfering with their daily activities. When designing a monitoring system, system performance reliability for competent healthcare is critical. Existing research has failed to create a large device capable of handling a large network or to improve WBAN topologies for fast transmitting and receiving patient data. As a result, in this research, we create a multisensor WBAN (MSWBAN) intelligent system for transmitting and receiving critical patient data. To gather information from all cluster nodes and send it to multisensor WBAN, a novel additive distance-threshold routing protocol (ADTRP) is proposed. In small networks where data are managed by the transmitting node and the best data route is determined, this protocol has less redundancy. An edge-cutting-based routing optimization (ES-EC-R ES-EC-RO) is used to find the best route. The Trouped blowfish MD5 (TB-MD5) algorithm is used to encrypt and decrypt data, and the encrypted data are stored in a cloud database for security. The performance metrics of our proposed model are compared to current techniques for the best results. End-to-end latency is 63 ms, packet delivery is 95%, security is 95.7%, and throughput is 9120 bps, according to the results. The purpose of this article is to encourage engineers and front-line workers to develop digital health systems for tracking and controlling virus outbreaks.

show abstract

Big Data Analytics for Large Scale Wireless Body Area Networks; Challenges, and Applications

Cited by 11 publications

References 21 publications

A Deep learning approach for trust-untrust nodes classification problem in WBAN

A Deep learning approach for trust-untrust nodes classification problem in WBAN

A secure telemedicine electronic platform based on lightweight cryptographic approach

Remote Monitoring of COVID-19 Patients Using Multisensor Body Area Network Innovative System

Contact Info

Product

Resources

About