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Wireless Body Area Networks (WBANs) are increasingly employed in different medical applications, such as remote health monitoring, early detection of medical conditions, and computer assisted rehabilitation. A WBAN connects a number of sensor nodes implanted in and/or fixed on the human body for monitoring his/her physiological characteristics. Alt...
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... Because of that broadcast, a single common key is generated for all the nodes in the WBAN, reducing the storage and communication overheads. In [21], the sensors use their previous session pre-knowledge for secure communication within a specific period of time reducing the time required for establishing the shared key. In [22], a low memory symmetric-key generation (LORENA) method based on group secret key agreement protocol for devices acquiring vital signs is proposed. ...
Wireless body area networks (WBANs) are becoming more and more popular since they allow people to continuously monitor their vital signs and physiological parameters remotely. The market for wearable heart rate monitors and portable pulse oximeters has exploded since the SARS-CoV-2 pandemic broke out. Additionaly, there has been an unprecedented increase of healthcare information breaches which revealed the extreme vulnerability of the current generation of WBANs. Therefore, it is imperative to design new security protocols to guarantee data confidentiality, authentication, integrity, and privacy within WBANs. Here, we target a WBAN collecting ECG signals from different sensor nodes on the individual's body and we develop a novel information theoretic key agreement protocol that exploits the inherent randomness of ECG to share secret cryptographic keys between sensor pairs within a WBAN. After proper pre-processing, we observe that the direct use of the ECG signals instead of some features extracted from them (e.g., IPIs) for the key generation can provide higher key rates, in general. In particular, we find a key rate that is at least 3 times that found using IPIs. Furthermore, we show that by considering a variable code rate during reconciliation, we are able to further increase the key generation rate overcoming that obtained by from IPI sequences by one order of magnitude.
... Mobile terminals in the system are mostly connected to the internet through cellular networks, distributing perception tasks to participants' mobile phones. This approach not only leads to high data collection costs, consuming considerable user network traffic, reducing user enthusiasm, and impacting system usability but also imposes significant load pressure on cellular mobile networks [7]. ...
With the rapid development of mobile networks and widespread use of mobile devices, there is an increasing focus on assigning location-based tasks to mobile users in the context of Mobile Crowd Sensing (MCS). One of the primary challenges in MCS is task assignment, i.e., distributing tasks to suitable users for completion. However, existing work often assumes static offline scenarios where the spatiotemporal information of all users and tasks is pre-determined and known. Neglecting the dynamic spatiotemporal distribution of users and tasks can lead to suboptimal assignment results. In this study, we investigate a novel task assignment problem called Community Task Assignment (CTA). The objective is to enhance the effectiveness and precision of task distribution by considering the sociality of current users and distributing location-based tasks through communities. Initially, we partition users into different communities by abstracting and identifying behavior patterns through the computation of minimum spanning trees, connectivity parameters, and community cohesion. Subsequently, we calculate the match between perception tasks and community behavior pattern features, and task distribution is carried out by the central nodes of the communities based on this match. Experimental validation first confirms the effectiveness of the community partitioning algorithm. Compared to existing algorithms, the proposed method more accurately detects community structures with similar behavioral features in the network. Furthermore, a comparison with existing task assignment algorithms verifies the superiority of the proposed method in terms of average task completion time, task matching rate, and overall utility of task assignments.
... Different scenarios in WSN-based e-healthcare are summarized below [5]: 1) Daily life supervision -A properly configured WSN can detect the patient's activity and provide valuable feedback, allowing them to better organize their daily lives [6]. 2) In-hospital monitoring -The use of WSN technology and the establishment of a wireless body area network (WBAN) allows for comprehensive care and observation for patients who previously must be kept in the hospital for longer period but instead can be recorded and evaluated regularly by specialists [7]. In such cases, hospitals set up a static node so patients wearing the WSN appliance can stay linked to the monitoring centre while wandering around [8]. 3) In-home recovery monitoring following surgery: The WSN technology can provide normal readings of several biological parameters after the patient is sent home, allows for a faster and more accurate diagnosis of heart diseases, and raises the alarm if necessary [9]. ...
Healthcare monitoring systems in hospitals and other health facilities have grown significantly, and portable healthcare monitoring systems using emerging technologies such as Internet of Things (IoT) technologies have aided the advancement of healthcare monitoring systems. Many studies have focused on intelligent healthcare systems in an IoT context to improve components, including wearable sensors and hardware devices, intelligent data collecting and processing, and network connections. Even while these applications are necessary and helpful for enhancing wireless healthcare settings related to monitoring, detection, and diagnostics, it might be challenging to fully understand how IoT characteristics are currently intertwined with its architecture. Accordingly, this work adds to the academic literature by thoroughly reviewing all significant areas of wireless healthcare monitoring system advancements. This research also examines a state-of-the-art healthcare monitoring system component under IoT. One hundred and ninety-four related articles were collected and filtered based on the system components defined. This study includes a thorough review and a list of genuine concerns with novel critical solutions. The study can facilitate academics and practitioners by giving them direction and vital information for future research.
... In [62], Al-Saeed et al. introduced a key agreement scheme for facilitating secure data transfer among WBAN sensors. This protocol measures and verifies the physiological features at both the source and destination of the communications. ...
... The keys generated are K ecg , K master , K s , and K si . K ecg is the Randomly generated sequence NOT operation M. V. Karthikeyan et al. [22] ECG signal OR, AND, XNOR, NOR, SWAPPING, SHIFTING Sanaz Rahimi Moosavi et al. [23] R-peaks Shifting, XOR and AES algorithm is used Nur Adibah Saffa et al. [24] Random key generation Randon number generator Yasmeen Al-Saeed et al. [25] R-peaks One-way hashing function MD5 and SHA-265 ...
In wireless body area network health care applications, energy-constraint wearable devices are used to monitor patient physiological parameters. The security of the private health information of a person plays a significant role because if it is captured and read by an unauthorized person, the confidentiality of the patient data is lost. Therefore, there is a requirement to secure the data by performing encryption to transfer it into an unreadable form. Since the resources used for encryption should be kept to a minimum as the devices are attached to the human body, a lightweight encryption algorithm has to be used. Therefore, the generation of a unique key used for encryption plays a significant role. In work, generating a unique key uses the ECG values taken from MIT-BIH Arrhythmia database. Four unique keys are generated, which can be used for encryption. The uniqueness and randomness of the keys generated are proved using the runs test and frequency test within the block. Also, the average hamming distance calculated between the ECG keys generated from two different ECG signals is 62.5% (≈\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\approx$$\end{document} 80 bits), which proves the distinctiveness of the keys generated. Implementation of the work is performed using Matlab.
... Wireless Body Area Network (WBAN) is defined as a special purpose sensor network meant to function independently to connect together different sensors and device inside and outside of the body of a human being or patient [14]. According to the study [15], WBAN are sensing and monitoring nodes that can be worn that contain processing and computing capabilities. Article [16] states that sensors are planted around the human body monitoring different physiological parameters and these sensors are used for monitoring patients in healthcare systems. ...
... Article [16] states that sensors are planted around the human body monitoring different physiological parameters and these sensors are used for monitoring patients in healthcare systems. A WBAN architecture has the following features: (a) network around the body of a patient, (b) gateway also known as sink, (c) wide network i.e., intranet or internet network, and (d) graphical user interface (GUI) for medical and other healthcare practitioner's applications [15,16]. In healthcare uses, data rates for sensor are useful and each use has a best data rate, hence the network and protocols related should contain sufficient bandwidth for backing all uses. ...
... The two approaches used to improve end-to-end reliability in WBAN are (a) use of reliable transport protocols; and (b) use of redundant transmission and coding techniques [16]. In an attempt to overcome congestion of the network, tunable reliability with congestion control for information transport in wireless sensor networks (TRCCIT); real-time and reliable transport (RT2) protocol for wireless sensor, priority-based congestion control protocol for controlling upstream in wireless congestion (PCCP) and Prioritized Heterogeneous Traffic-Oriented Congestion Control Protocol (PHTCCP) networks have been discovered and used [15]. Congestion Detection and Avoidance (CODA) -has been defined by Rohrer [20] as an upstream congestion protocol that is energy efficient. ...
... The key management and design technology of encryption technology are improved At present, the research on network security is mostly based on the perspective of algorithms [10][11][12]. However, there are many perspectives on the research of network security, and it is also a direction that can combine the spread of malicious software with the dynamics of infectious diseases. ...
With the development of wireless sensor networks (WSNs), energy constraints and network security have become the main problems. This paper discusses the dynamic of the Susceptible, Infected, Low-energy, Susceptible model under pulse charging (SILS-P) in wireless rechargeable sensor networks. After the construction of the model, the local stability and global stability of the malware-free T-period solution of the model are analyzed, and the threshold R0 is obtained. Then, using the comparison theorem and Floquet theorem, we obtain the relationship between R0 and the stability. In order to make the conclusion more intuitive, we use simulation to reveal the impact of parameters on R0. In addition, the paper discusses the continuous charging model, and reveals its dynamic by simulation. Finally, the paper compares three charging strategies: pulse charging, continuous charging and non-charging and obtains the relationship between their threshold values and system parameters.
A Wireless Body Area Network (WBAN) is a network that expands over the human body, consisting of multiple nodes that are connected through wireless channels. It offers many applications in the area of remote health care. Maintaining the security of health information in WBAN is an essential requirement. One aspect of ensuring WBAN security is the generation of random binary sequences (RBSs), e.g., encryption keys generation. Due to the very limited resources of WBAN sensors, traditional pseudorandom number generators cannot be used. To reduce resource consumption, some researchers suggested using biometrics in generating RBSs, specifically the electrocardiogram (ECG) signal. However, their methods suffer from low throughput, so they are not suitable for real-time healthcare applications. In this paper, we present a new random sequence generator based on the ECG signal. Our contribution is to build a random sequence generator that generates different length RBSs and has throughput tens or hundreds of times higher than previous methods. Our generator reduces resource consumption due to its very simple processing operations. To evaluate the proposed generator, RBSs of different lengths (128, 256, 512, 1024, 2048 bits) were generated from two ECG datasets, the first is for healthy people, and the second is for people who suffer from arrhythmia. The randomness and distinctiveness of the generated RBSs are evaluated using the National Institute of Standards and Technology (NIST) statistical tests and the Hamming distance. Thus, we have proved that the resulting RBSs are appropriate for information security applications.
