Medical Sensor Nodes Research Articles

A full privacy-preserving distributed batch-based certificate-less aggregate signature authentication scheme for healthcare wearable wireless medical sensor networks (HWMSNs)

AbstractThe dynamic connectivity and functionality of sensors has revolutionized remote monitoring applications thanks to the combination of IoT and wireless sensor networks (WSNs). Wearable wireless medical sensor nodes allow continuous monitoring by amassing physiological data, which is very useful in healthcare applications. These text data are then sent to doctors via IoT devices so they can make an accurate diagnosis as soon as possible. However, the transmission of medical text data is extremely vulnerable to security and privacy assaults due to the open nature of the underlying communication medium. Therefore, a certificate-less aggregation-based signature system has been proposed as a solution to the issue by using elliptic curve public key cryptography (ECC) which allows for a highly effective technique. The cost of computing has been reduced by 93% due to the incorporation of aggregation technology. The communication cost is 400 bits which is a significant reduction when compared with its counterparts. The results of the security analysis show that the scheme is robust against forging, tampering, and man-in-the-middle attacks. The primary innovation is that the time required for signature verification can be reduced by using point addition and aggregation. In addition, it does away with the reliance on a centralized medical server in order to do verification. By taking a distributed approach, it is able to fully preserve user privacy, proving its superiority.

A Security-Enhanced and Privacy-Preserving Certificateless Aggregate Signcryption Scheme-Based Artificial Neural Network in Wireless Medical Sensor Network

With the recent advances in mobile sensing and beyond-5G technologies, wireless medical sensor networks (WMSNs) have become an emerging hot topic in smart healthcare. Under the condition of limited resources of medical sensor nodes (MSNs), ensuring the accuracy and integrity of a large number of patients’ medical data is a crux for security and data privacy issues. In order to overcome the limitations of medical sensors in communication and computing capabilities, and to achieve privacy in WMSN, we propose a low complexity certificateless aggregate signcryption (CL-ASC) scheme-based artificial neural network (NN) for safely achieving authentication and unforgeability of medical nodes. We use an adaptive sigma filter for denoising, adopt Levenshtein entropy for encoding, and design cryptographic protocol for signcrypting in the hidden layer of deep feedforward artificial NN (DFANN). The CL-ASC can authenticate all sensing bioinformation at once in a privacy-preserving way. Given the challenge of applying a discrete logarithm and computational Diffie-Hellman problems based on an elliptic curve, the proposed scheme satisfies the indistinguishability against chosen-ciphertext attacks (IND-CCA) and the adaptive chosen message attack (UF-CMA) security properties under the random oracle model (ROM). Finally, the benchmark evaluation shows that ours is ahead of similar state-of-the-art schemes, due to its low complexity and higher computational efficiency. Researchers interested in the provable security protocol design and framework of NNs can gain useful insights from this research and identify future cross domain of cybersecurity and NNs research directions based on the proposed scheme herein.

Trustable Body Area Network for Emergency Response

In the medical field, Wireless Body Area Networks (WBAN) play the main role in keeping users healthy by offering convenient services for doctors and patients. However, the attacker is prevented from tampering with the sensor data by communicating through an unsecured channel, which prevents the forwarded packets from their hazardous origins. Several methods of safe authentication are suggested for bolstering the trustworthiness of the channels of communication in protecting user data. A Trustable Body Area Network (TBAN) for Emergency Response approach to protect the medical sensor nodes from untrusted nodes and increase efficiency. Simple trust and compound trust computations are used to isolate untrustable nodes. In addition, this system applies a hash-based signature with a onetime password to confirm the second-level sensor node authentication in the WBAN. The simulation result demonstrates that the proposed system detects the untrustable sensor node efficiently and reduces the network delay.

An improved pairing-free certificateless aggregate signature scheme for healthcare wireless medical sensor networks.

In healthcare wireless medical sensor networks (HWMSNs), the medical sensor nodes are employed to collect medical data which is transmitted to doctors for diagnosis and treatment. In HWMSNs, medical data is vulnerable to various attacks through public channels. In addition, leakage of patients’ information happens frequently. Hence, secure communication and privacy preservation are major concerns in HWMSNs. To solve the above issues, Zhan et al. put forward a pairing-free certificateless aggregate signature (PF-CLAS) scheme. However, according to our cryptanalysis, the malicious medical sensor node (MSNi) can generate the forged signature by replacing the public key in the PF-CLAS scheme. Hence, to address this security flaw, we design the improved PF-CLAS scheme that can achieve unforgeability, anonymity, and traceability. Since we have changed the construction of the partial private key, the improved PF-CLAS scheme can resist Type I and Type II attacks under the Elliptic Curve Discrete Logarithm assumption. In terms of the performance evaluation, the proposed scheme outperforms related CLAS schemes, which is more suitable for HWMSNs environments.

Design and Implementation of Remote Real-Time Monitor System for Prosthetic Limbs

Persons with Lower-limb amputations experience movement restrictions resulting in worsening their life quality. Wearable sensors are often utilized to evaluate spatial and temporal qualities and kinetic parameters that provide the mechanism to create interactive monitoring of the amputee prosthesis system. Gait events and detection of the gait phase of amputee movement are essential to control the prosthetic devices of lower limbs. This paper presents real-time monitoring to individuals with lower limb amputation by using a medical wireless sensor. However, the proposed system used four medical sensor nodes (such as gait, temperature, the pressure of blood, blood oxygenation (SpO2) )for transmitted medical data by the RFB 24 to the sink node to collected data and upload by ESP32 to the Local cloud ( Raspberry pi 4) by using Wi-Fi network, then design the web application for enable the doctor monitor the patient (lower-limb amputation (LLA)) and provide the reporter to on each patient, where local cloud provides the data to the web application. The conduction of this work is using one sink node to four nodes (patient) to reduce the data rate and the energy consumption. In this work, one IP to four medical sensor nodes lowers the data rate to 60%, and the energy consumption by the sensing nodes is lowered by 20% that using one IP instead of using five IP reduce the size of the transmitted packet.

Hybrid Energy Harvester for Medical Sensor Node toward Real-Time Healthcare Monitoring

In healthcare applications, the remote monitoring for moving patients depends on medical sensor nodes, which should be mobile. Thus, the power mains of medical sensor nodes should be disconnected most of the time to monitor natural movements of patients. In this paper, a self-sustainable medical sensor node is proposed for healthcare monitoring applications. The node implementation consists of a microcontroller unit (MCU), a photo-plethysmography (PPG) sensor, a Bluetooth low energy (BLE) module, and a MPU module that includes a gyroscope with accelerometer. The power supply of the node is a hybrid energy harvester developed to provide a sustainable energy for the sensor node. The harvester is composed of a photovoltaic (PV) panel, a thermoelectric generator (TEG) module, a DC-DC converter, and a super-capacitor. Experimental results illustrate that the proposed node can monitor a physiological data on a mobile device using the BLE Terminal application.

Network Performance Measurement through Machine to Machine Communication in TeleRobotics System

Machine-to-machine (M2M) communication devices communicate and exchange information with each other in an independent manner to perform necessary tasks. The machine communicates with another machine over a wireless network. Wireless communication opens up the environment to huge vulnerabilities, making it very easy for hackers to gain access to sensitive information and carry out malicious actions. This paper proposes an M2M communication system through the internet in Tele-Robotics and provides network performance security. Tele-robotic systems are designed for surgery, treatment and diagnostics to be conducted across short or long distances while utilizing wireless communication networks. The systems also provide a low delay and secure communication system for the tele-robotics community and data security. The system can perform tasks autonomously and intelligently, minimizing the burden on medical staff and improving the quality and system performance of patient care. In the medical field, surgeons and patients are located at different places and connected through public networks. So the design of a medical sensor node network with LEACH protocol for secure and reliable communication ensures through the attack and without attack performance. Finally, the simulation results show low delay and reliable secure network transmission.

Secured energy efficient machine -to-machine communication for telerobotic system

Machine-to-Machine (M2M) communication refers to applications that run on intelligent devices or machines. It allows smart devices to communicate directly with each other with little or no human intervention.In a telerobotic system, medical devices interact with each other and exchange information automatically to provide visual assistance to physicians during surgery. Wireless communication provides attackers with numerous options to gain access to sensitive data and carry out malicious operations.A small communication delay in the telerobotic system can have a significant impact on the performance of medical equipment, potentially putting the patient's life in danger. Additionally, it can slow down the entire system in an operating room. Here, an energy-efficient and secured M2M network is presented to make the system robust.The system is designed with Event-Driven Duty Cycling (EDDC) routing protocol for enhancing the energy of medical sensor nodes. A Denial-of-Service (DoS) attack is performed and network performance is measured through Quality of Service (QoS) parameters. The results of the proposed routing protocol are compared with those of the LEACH and ECFU.The EDDC protocol outperforms even when attacks are launched.

Cryptanalysis and Improvement of a Pairing-Free Certificateless Aggregate Signature in Healthcare Wireless Medical Sensor Networks

The healthcare wireless medical sensor network is gradually changing the traditional mode of medical treatments with the rapid development of Internet of Things. Specifically, patients' healthcare data can be continuously collected by medical sensor nodes and transmitted to the medical specialists for disease monitoring, diagnosis and treatments. Recently, due to its advantages of low computational and communication overheads in a multiuser environment, the certificateless aggregate signature (CLAS) scheme has been adopted to prevent the sensitive healthcare data from being tampered and damaged, thereby ensuring the integrity and authenticity of data. In order to further improve the efficiency of CLAS schemes for the sensor nodes with limited resources, several CLAS schemes without bilinear pairing have been proposed. However, security issues prevent them from being fully applied in the practical scenarios. In this article, we analyze the security of a pairing-free CLAS scheme proposed by Liu et al. [IEEE Internet of Things Journal, vol. 7, no. 6, pp. 5256-5266, 2020] by pointing out that their scheme is insecure against adversaries. After that, we introduce an improved scheme to solve the security vulnerability. The security proofs show that our improved scheme is existentially unforgeable against chosen message attacks under the random oracle model. In addition, the length of the aggregate signature in our proposal does not increase with the growth of the number of users, which greatly reduces the communication cost. Finally, the efficiency of our scheme is illustrated through both performance analyses and comparisons of related work.

Energy-Aware WBAN for Health Monitoring Using Critical Data Routing (CDR)

Wireless body area network (WBAN) is the subfield of Wireless Sensor Network, employs in the area of monitoring the health of the patient. WBAN is also known as wireless body sensor network in which sensor nodes are fused inside the body of the person to detect their physiological changes. After processing or comparing those obtained data with the pre-stored default value, the packets are transmitted to the base station. Due to the inner-body sensor node, replacement of the battery may hazardous for the person. So, storing up and saving of energy is the main focus inside the WBANs. In this research, we employ the critical data routing code for transmitting the relevant data from inner-body node to the on-body medical super sensor (MSS) node. Here, MSS act as a controller that can manage all the injected sensor node inside the body of the person as their member. And, if inner-body sensor node is detecting any corporal activities from the human body then it compares those data with the pre-stored threshold level value of that sensor node, and if sensor obtained more deviation in their results then it follows the critical data routing (CDR) for the transmission process, unless it goes to the rest mode. In other words, the sensor node can only be transmitted the critical packet data to their near-by controller and avoiding the redundant picking of normal packet data. By following this procedure we can save the maximum of energy for the sensor so that it alive for the greatest period of time that lead to continuous monitoring of the patient and also maximizes the lifespan of the network. Simulation can be done on MATLAB that can show the finest outcomes in terms of energy spending, network lifespan, throughput- efficiency, hold up by any one of the steering protocol when there is a comparison between CDR, REEC, and SIMPLE respectively.

Efficient and Secure Pairing-Free Certificateless Aggregate Signature Scheme for Healthcare Wireless Medical Sensor Networks

Recent advancements in wireless communication technologies have led to the development of practical applications, such as infrastructure monitoring, earthquake monitoring, environment monitoring, remote healthcare monitoring, etc. In these applications, we may integrate the wireless sensor networks (WSNs) with Internet of Things (IoT), where sensor nodes join the Internet dynamically and use it to collaborate and accomplish their tasks. In e-healthcare system, wireless medical sensor nodes continuously monitor and collect the physiological information and transmit the same to healthcare professionals through IoT terminals. To overcome the limitations in communication and computational capabilities in sensors and to attain privacy in healthcare wireless medical sensor networks (HWMSNs), few signature schemes were proposed in the literature. However, most of these schemes are insecure against various attacks. Hence to ensure privacy and security in medical data, in this paper, we proposed an efficient pairing-free aggregate signature scheme for HWMSNs in certificateless system. We exploit aggregation technique in certificateless system without using pairings to reduce computational complexity and transmission overhead in transferring the data. Our scheme achieves full aggregation to improve communicational efficiency and performance analysis shows that the proposed scheme is more efficient.

Autonomous monitoring in healthcare environment: Reward-based energy charging mechanism for IoMT wireless sensing nodes

Abstract The Internet of Medical Things (IoMT) is an essential paradigm for ubiquitous monitoring in healthcare environments. The IoMT system collects data (e.g. temperature, hazardous contamination, light intensity, room and patient status, etc.) from connected medical devices and sensor nodes to a central or distributed computer network. In order for these devices and sensor nodes to continue operating, they must be charged with sufficient energy at all times. In this paper, we propose an IoMT system that employs autonomous mobile chargers, which is equipped with wireless energy transfer technology, to support sensor nodes recharging requests. In this model, the mobile charger must distribute the energy among the sensor nodes so that their operation is not interrupted. This is challenging because the mobile charger carries limited amount of energy that may not be sufficient to satisfy all recharging requests. In this paper, we propose a reward-based energy charging decision mechanism that allows mobile chargers and sensor nodes to coordinate the charging process. The proposed reward-based mechanism utilizes the Analytical Hierarchy Process (AHP) for fair distribution of energy among the nodes. This paper presents the theoretical analysis of the model and the simulation experiments. Our results show that the proposed model can support a larger number of active nodes with less energy compared to conventional first come first served methods. Also the coverage utility of sensor nodes is much higher using our method compared to the on-demand recharging request schemes found in existing studies.

On the Design of Low-Cost IoT Sensor Node for e-Health Environments

The proliferation of Internet of Things (IoT) devices for patient monitoring has gained much attention in clinical care performance, proficient chronic disease management, and home caregiving. This work presents the design of efficient medical IoT sensor nodes (SNs) in terms of low-cost, low power-consumption, and increased data accuracy based on open-source platforms. The method utilizes a Sensor Controller (SC) within the IoT SN, which is capable of performing medical checks supporting a broad coverage of medical uses. A communication protocol has been developed for data and command exchange among SC, local gateways, and physicians’ or patients’ mobile devices (tablets, smart phones). The SC supports moving average window (MAW) and principle component analysis (PCA) filtering algorithms to capture data from the attached low-cost body sensors of different sampling profiles. Significant extensions in SN’s portability is achieved through energy consumption minimization based on the idle time gaps between sensors’ activations. SN’s components are either deactivated or set to low activity operation during these idle intervals. A medical case study is presented and the evaluated results show that the proposed SN can be incorporated into e-health platforms since it achieves comparable accuracy to its certified and high-cost commercial counterparts.

An Improved Three-Factor User Authentication and Key Agreement Scheme for Wireless Medical Sensor Networks

As wireless communication technology and semiconductor technology developed fast, the wireless medical sensor networks (WMSNs) have been applied to the modern health-care area at large. The physiological data can be obtained by medical sensor nodes deployed in the patient’s body and sent to the special devices of the health professionals through wireless communication. Thus, the status of a patient is monitored by the health professional in that way. However, there are still two important issues that how to guarantee secure communication and protect the privacy of the patient for the reason of the open feature of wireless communication. In this paper, initially, an improved three-factor user authentication scheme is proposed to overcome those flaws utilizing password, smart card, and biometric feature. Furthermore, formal security analysis shows that the proposed scheme defends against various security pitfalls. Finally, the comparison results with other surviving relevant schemes show that our scheme is more efficient in terms of computational cost, communication cost, and estimated time. Therefore, the proposed scheme is suitable for practical application in WMSN.

Context Aware Trust Management Scheme for Pervasive Healthcare

Medical sensor nodes are used in pervasive healthcare applications like remote patient monitoring, elderly care to collect patients vital signs for identifying medical emergency. These resource restricted sensor nodes are prone to various malicious attacks, data faults and data losses. Presence of faulty data, data loss in collected patient data may lead to incorrect analysis of patient condition, which decreases the reliability of pervasive healthcare system. The aim of this work is to alert the caregiver and raise the alarm only when the patient enters into medical emergency situation. The proposed scheme also reduces the false alarms and alerts caused by data fault and misbehaving sensor nodes. To achieve this, we introduce a context aware trust management scheme for data fault detection, data reconstruction and event detection in pervasive healthcare systems. It employs heuristic functions, data correlation and contextual information based algorithms to identify the data faults and events. It also reconstructs the data faults and data loss for identifying patient condition. Performance of this approach is evaluated with the help of real data samples collected by medical sensor network prototype of remote patient monitoring application. The experimental results show that the proposed trust scheme outperforms state-of-the-art techniques and achieves good detection accuracy in data fault detection and event detection.

Survey on power analysis attacks and its impact on intelligent sensor networks

Smart or intelligent sensors are integrated physical units embedded with sensors, processors, and communication devices. The sensors also known as edge nodes form the lower-most tier in the internet of things architecture. These devices rely on cryptographic technique to ensure ‘root of trust’ for the users. The implementation attacks namely side-channel attacks (SCAs) pose a dangerous threat for the cryptographic implementation in the edge nodes since the attacks are undetectable by nature. Among the different categories of SCAs proposed in the literature, power analysis attacks (PAAs) are vastly studied and widely employed because it can be mounted with relatively inexpensive equipment. In this study, the different categories of PAAs along with the countermeasures are reviewed in detail. The impact of the SCA on the edge nodes is examined along with a case study on medical sensor nodes.

FSO–PSO based multihop clustering in WSN for efficient Medical Building Management System

A Wireless Sensor Network (WSN) is the one that is formed keeping a maximum number of sensor nodes that have been positioned in any application or an environment for monitoring the physical entities in the target area. The main challenge is the organizing of sensor networks with efficacy of energy. This need for efficacy of energy is owing to the capacity of the sensor node being limited and their replacement not being viable. An efficient technique to prolong the lifetime of WSNs is by means of adapting clustering algorithm. This includes the grouping of sensor nodes into clusters and the electing of Cluster Heads (CH) and the forwarding of their aggregated data to that of the Base Station (BS). A challenge involved in the WSN is the choice of suitable CH. Building Management Systems are a control system that is computer-based and installed in buildings which tend to control and also monitor the mechanical as well as the electrical equipment of the building like the ventilation, power systems, lighting etc., Medical sensor nodes have been used for examine several signals from a human body to monitor parameters like blood pressure, body temperature, blood sugar, pulse oxygenation of the blood etc. The work proposed the Fish Swarm Optimization (FSO), the Particle Swarm Optimization (PSO) that is based on multi-hop clustering algorithm for the saving energy consumption in WSN. When the visual and the step dominated the FSO they are quite challenging to be set as well. The work employs the PSO formulation for modifying the FSO and make is free from step. Also, visual along with the searching domain is formulated to improve ease of setting. The results of the experiment show that this method has better performance.

Performance Analysis of End-to-End Security Schemes in Healthcare IoT

In this paper, we analyze the performance of the state-of-the-art end-to-end security schemes in healthcare Internet of Things (IoT) systems. We identify that the essential requirements of robust security solutions for healthcare IoT systems comprise of (i) low-latency secure key generation approach using patients’ Electrocardiogram (ECG) signals, (ii) secure and efficient authentication and authorization for healthcare IoT devices based on the certificate-based datagram Transport Layer Security (DTLS), and (iii) robust and secure mobility-enabled end-to-end communication based on DTLS session resumption. The performance of the state-of-the-art security solutions including our end-to-end security scheme is tested by developing a prototype healthcare IoT system. The prototype is built of a Pandaboard, a TI SmartRF06 board and WiSMotes. The Pandaboard along with the CC2538 module acts as a smart gateway and the WisMotes act as medical sensor nodes. Based on the analysis, we found out that our solution has the most extensive set of performance features in comparison to related approaches found in the literature. The performance evaluation results show that compared to the existing approaches, the cryptographic key generation approach proposed in our end-to-end security scheme is on average 1.8 times faster than existing key generation approaches while being more energy-efficient. In addition, the scheme reduces the communication overhead by 26% and the communication latency between smart gateways and end users by 16%. Our scheme is also approximately 97% faster than certificate based and 10% faster that symmetric key-based DTLS. Certificate based DTLS requires about 2.9 times more ROM and 2.2 times more RAM resources. On the other hand, the ROM and RAM requirements of our scheme are almost as low as in symmetric key-based DTLS.

Link quality aware channel allocation for multichannel body sensor networks

Body Sensor Network (BSN) is a typical Internet-of-Things (IoT) application for personalized health care. It consists of economically powered, wireless and implanted medical monitoring sensor nodes, which are designed to continually collect the medical information of the target patients. Multichannel is often used in BSNs to reduce the spectrum competition of the tremendous sensor nodes and the problem of channel assignment has attracted much research attention. The health sensing data in BSNs is often required to be delivered to a sink node (or server) before a certain deadline for real time monitoring or health emergency alarm. Therefore, deadline is of significant importance for multichannel allocation and scheduling. The existing works, though designed to meet the deadline, often overlook the impact of the unreliable wireless links. As a result, the health sensing data can still be overdue because of the scheduled lossy links. Besides, potential collisions in the schedules also incur considerable delay in delivering the sensing data. In this paper, we propose a novel deadline-driven Link quality Aware Channel Assignment scheme (LACA), where link quality, deadlines and collisions are jointly considered. LACA prioritizes links with urgent deadlines and heavy collisions. Besides, LACA allows the exploitation of the spare slots for retransmissions on lossy links, which can further reduce the retransmission delay. Extensive simulation experiments show that compared to the existing approaches, LACA can better utilize the wireless spectrum and achieve higher packet delivery ratio before the deadline.

SEA: A Secure and Efficient Authentication and Authorization Architecture for IoT-Based Healthcare Using Smart Gateways

In this paper, a secure and efficient authentication and authorization architecture for IoT-based healthcare is developed. Security and privacy of patients’ medical data are crucial for the acceptance and ubiquitous use of IoT in healthcare. Secure authentication and authorization of a remote healthcare professional is the main focus of this work. Due to resource constraints of medical sensors, it is infeasible to utilize conventional cryptography in IoT-based healthcare. In addition, gateways in existing IoTs focus only on trivial tasks without alleviating the authentication and authorization challenges. In the presented architecture, authentication and authorization of a remote end-user is done by distributed smart e-health gateways to unburden the medical sensors from performing these tasks. The proposed architecture relies on the certificate-based DTLS handshake protocol as it is the main IP security solution for IoT. The proposed authentication and authorization architecture is tested by developing a prototype IoT-based healthcare system. The prototype is built of a Pandaboard, a TI SmartRF06 board and WiSMotes. The CC2538 module integrated into the TI board acts as a smart gateway and the WisMotes act as medical sensor nodes. The proposed architecture is more secure than a state-of-the-art centralized delegation-based architecture because it uses a more secure key management scheme between sensor nodes and the smart gateway. Furthermore, the impact of DoS attacks is reduced due to the distributed nature of the architecture. Our performance evaluation results show that compared to the delegation-based architecture, the proposed architecture reduces communication overhead by 26% and communication latency from the smart gateway to the end-user by 16%.