Wireless Medical Sensor Research Articles

A Mutual Authentication Framework for Wireless Medical Sensor Networks.

Wireless medical sensor networks (WMSN) comprise of distributed sensors, which can sense human physiological signs and monitor the health condition of the patient. It is observed that providing privacy to the patient's data is an important issue and can be challenging. The information passing is done via the public channel in WMSN. Thus, the patient, sensitive information can be obtained by eavesdropping or by unauthorized use of handheld devices which the health professionals use in monitoring the patient. Therefore, there is an essential need of restricting the unauthorized access to the patient's medical information. Hence, the efficient authentication scheme for the healthcare applications is needed to preserve the privacy of the patients' vital signs. To ensure secure and authorized communication in WMSN, we design a symmetric key based authentication protocol for WMSN environment. The proposed protocol uses only computationally efficient operations to achieve lightweight attribute. We analyze the security of the proposed protocol. We use a formal security proof algorithm to show the scheme security against known attacks. We also use the Automated Validation of Internet Security Protocols and Applications (AVISPA) simulator to show protocol secure against man-in-the-middle attack and replay attack. Additionally, we adopt an informal analysis to discuss the key attributes of the proposed scheme. From the formal proof of security, we can see that an attacker has a negligible probability of breaking the protocol security. AVISPA simulator also demonstrates the proposed scheme security against active attacks, namely, man-in-the-middle attack and replay attack. Additionally, through the comparison of computational efficiency and security attributes with several recent results, proposed scheme seems to be battered.

Minimizing Path Loss in Medical Wireless Sensors in Wireless Body Area Sensor Networks

Objectives: To save the energy consumption of the sensors in transmission so that they may operate for longer time span. Methods/Statistical Analysis: It is suggested to use eight sensors placed on the human body and then transposition has been applied to all of these sensors to reduce the distance of each sensor from the sink. Path loss was calculated after transposition in terms of distance and results were compared with the existing schemes. Euclidean distance technique was applied to calculate the distance values and then observed for their positions. Findings: In this investigation, the main parameter is the path loss which needs to be reduced so as to make the transmission better and to make network stable. The findings are unique in the sense that with the help of the proposed values of sensor positions a routing protocols be designed which will have a better network stability and network life time and this will be achieved as the sensors will deplete less energy during transmission. The main idea behind this research is to find the most suitable sensor locations on the body where they can consume less energy during data transmission to sink and have more life to operate. Application/Improvements: The proposed scheme is applicable to body area systems which have limited energy sources due to the size of the sensors. The proposed scheme is compared with two existing schemes and there were improvements in terms of path loss parameter.

SI-Based Class AB Power Amplifier for Wireless Medical Sensor Network

SI-Based Class AB Power Amplifier for Wireless Medical Sensor Network

Privacy-Preserving Data Communication Through Secure Multi-Party Computation in Healthcare Sensor Cloud

In recent years, wireless medical sensor networks meet the web to enable exciting healthcare applications that require data communication over the Internet. Often these applications suffer from data disclosure due to malicious users’ activities. To prevent such data disclosure in the healthcare systems, many public key cryptographic techniques have been used. However, most of them are too expensive to implement in the web-enabled wireless medical sensor networks. In 2013, Xun et al. introduced a lightweight encryption algorithm to protect communication between the sensor node and the data servers. Their scheme is based on the Sharemind framework. However, Sharemind framework has a limitation on the number of data storage servers (ie., three servers only). In addition, Xun et al’s scheme does not support privacy-preserving patient data analysis for distributed databases of different hospitals. In this paper, we introduce a new practical approach to prevent data disclosure from inside attack. Our new proposal is based on FairplayMP framework which enables programmers who are not experts in the theory of secure computation to implement such protocols. In addition, it support any number of n participants and is suitable for distributed environments. Moreover, in our new scheme, each sensor node needs only one secret key stored in advance to communicate with n different data servers, whereas three secret keys are embedded in advance into each sensor in order to communicate with three data servers in Xun et al’s scheme.

A Secure Smartcard-Based Anonymous User Authentication Scheme for Healthcare Applications Using Wireless Medical Sensor Networks

A wireless medical sensor network (WMSN ) is a professional application of the traditional wireless body area sensor networks in medicine. Using WMSNs, the parameters of patients' vital signs can be gathered from the sensor nodes deployed on the body of the patients and accessed by the healthcare professionals by using a mobile device. Due to wireless communication, securing communication becomes a vital issue in WMSNs. Since the vital signs parameters are sensitive to the patients' health status and these information must not be revealed to the others except the healthcare professionals, the protection of patients' privacy becomes another key issue for WMSNs applications. Thus, user authentication with anonymity property is the most basic and commonly used method in order to resolve the security and privacy issues of WMSNs. He et al. presented a user authentication protocol for healthcare applications using WMSNs to protect the security and privacy problems. However, Li et al. showed that their scheme is incorrect in authentication and session key agreement phase, has no wrong password detection mechanism and is vulnerable to denial of service caused by password change with wrong password. In this paper, we review Li et al.'s scheme and show that their scheme is still vulnerable to privileged-insider attack, sensor node capture attack and fails to provide user anonymity property. Moreover, we find that He et al.'s scheme is still vulnerable to the same attacks as we find out in Li et al.'s scheme. In order to remedy the security weaknesses found in both He et al.'s scheme and Li et al.'s scheme, we present a secure biometrics-based user authentication scheme in WMSNs using smart card. Through the rigorous formal and informal security analysis, we show that our scheme is secure against possible known attacks. In addition, we simulate our scheme using the most-widely accepted and used Automated Validation of Internet Security Protocols and Applications tool and the simulation results reveal that our scheme is secure. Our scheme is also efficient in computation and communication as compared to He et al.'s scheme, Li et al.'s scheme and other related schemes.

Implementation of Aggregate Signcryption in Unattended Medical WSNs using Micaz

Healthcare applications are promising fields for wireless sensor networks called wireless medical sensor networks. The main issues in wireless medical sensor networks are reliable communication, patient mobility and security of sensed physiological data. In order to mobile patient monitoring, disconnected or unattended setting of wireless medical sensor networks is considered. The disconnected property causes periodic or offline data delivery of information. Moreover, medical sensors nodes should retain data for long time while they have limited battery and capacity. These challenges provide attacker to threat security of sensed data without being detected. In this paper, we propose an efficient aggregate signcryption technique to provide simultaneously confidentiality, integrity (by encrypting) and authenticating (by signing) for collected data. Moreover, the aggregation property reduces communication and space overhead as well as signcryption provides time efficiency by applying mostly linear operators. We further, compare our technique with the nest alternative works in the literature to show the efficiency and resilience against various attacks

Mobile health: the power of wearables, sensors, and apps to transform clinical trials.

Mobile technology has become a ubiquitous part of everyday life, and the practical utility of mobile devices for improving human health is only now being realized. Wireless medical sensors, or mobile biosensors, are one such technology that is allowing the accumulation of real-time biometric data that may hold valuable clues for treating even some of the most devastating human diseases. From wearable gadgets to sophisticated implantable medical devices, the information retrieved from mobile technology has the potential to revolutionize how clinical research is conducted and how disease therapies are delivered in the coming years. Encompassing the fields of science and engineering, analytics, health care, business, and government, this report explores the promise that wearable biosensors, along with integrated mobile apps, hold for improving the quality of patient care and clinical outcomes. The discussion focuses on groundbreaking device innovation, data optimization and validation, commercial platform integration, clinical implementation and regulation, and the broad societal implications of using mobile health technologies.

Security and privacy in Internet of things: methods, architectures, and solutions

Security and privacy in Internet of things: methods, architectures, and solutions

A robust and anonymous patient monitoring system using wireless medical sensor networks

In wireless medical sensor network (WMSN), bio-sensors are implanted within the patient body to sense the sensitive information of a patient which later on can be transmitted to the remote medical centers for further processing. The patient’s data can be accessed using WMSN by medical professionals from anywhere across the globe with the help of Internet. As the patient sensitive information is transmitted over an insecure WMSN, so providing a secure access and privacy of the patient’s data are challenging issues in WMSN environments. However, in literature, to provide secure data access, few user authentication protocols exist. Most of these existing protocols may not be applicable to WMSNs for providing user’s anonymity. To fill these gaps, in this article, we propose an architecture for patient monitoring health-care system in WMSN and then design an anonymity-preserving mutual authentication protocol for mobile users. We used the AVISPA tool to simulate the proposed protocol. The results obtained indicate that the proposed authentication protocol resists the existing well known attacks. In addition, the BAN logic model confirms mutual authentication feature of the proposed protocol. Moreover, an informal cryptanalysis is also given, which ensures that the proposed protocol withstands all known attacks. We perform a comparative discussion of the proposed protocol against the existing protocols and the comparative results demonstrate that the proposed protocol is efficient and robust. Specifically, the proposed protocol is not only effective in providing robustness against common security threats, but it also offers an efficient login, robust mutual authentication, and user-friendly password change.

Privacy Protection for Wireless Medical Sensor Data

In recent years, wireless sensor networks have been widely used in healthcare applications, such as hospital and home patient monitoring. Wireless medical sensor networks are more vulnerable to eavesdropping, modification, impersonation and replaying attacks than the wired networks. A lot of work has been done to secure wireless medical sensor networks. The existing solutions can protect the patient data during transmission, but cannot stop the inside attack where the administrator of the patient database reveals the sensitive patient data. In this paper, we propose a practical approach to prevent the inside attack by using multiple data servers to store patient data. The main contribution of this paper is securely distributing the patient data in multiple data servers and employing the Paillier and ElGamal cryptosystems to perform statistic analysis on the patient data without compromising the patients’ privacy.

(Invited) Self-Powered, Wireless Medical Sensor and Devices

Implantable medical devices and integrated wireless healthcare sensors are attracting extensive attention, but the batteries used for powering these devices usually display a limited lifetime. Although battery technology has improved, sustainable power sources for cardiac pacemakers, neural stimulators and other implantable biomedical devices are required. Mechanical energy was considered as one of most abundant and accessible energy sources around the human body. When a small system can efficiently convert mechanical energy in our daily life, this system would be a suitable solution for electricity generation and significantly extend the lifetime of the electronic devices, especially in medical area. Recently, triboelectric nanogenerator (TENG) has attracted much attention and been considered as another potential solution for harvesting mechanical energy. With its high output performance, outstanding biocompatibility and low cost, TENG has been studied for powering implantable medical electronic devices. Here, we demonstrated an in vivo biomechanical-energy harvesting using a TENG. An implantable triboelectric nanogenerator (iTENG) in a living animal has been developed to harvest energy from its periodic breathing. We also developing an encapsulation method for protecting iTENG from the contamination or liquid infiltration of the surrounding environment. Another important consideration is the versatility of the energy harvesters, which can facilitate the integration between iTENG and the various implantable medical electronics and promote the development of self-powered implantable medical devices and wearable/portable electronics. We also designed viable inner connections and universal outlet connectors for the system. The power management elements and NG were integrated on a flexible substrate; therefore, the entire system could be a “Plug and Play” mobile power source. The system was also packaged by PDMS as a waterproof implantable full energy unit for implantable medical electronic devices. The energy generated from breathing and body moving was used to power a prototype pacemaker and a low-level laser cure (SPLC) system, respectively. It was found that the self-powered system could regulate the heart rate of a rat and significantly accelerated the mouse embryonic osteoblasts' proliferation and differentiation. This is a significant progress for fabricating self-powered implanted medical electronic devices using TENG as a power source. Figure 1

Secure Authentication for Remote Patient Monitoring with Wireless Medical Sensor Networks.

There is broad consensus that remote health monitoring will benefit all stakeholders in the healthcare system and that it has the potential to save billions of dollars. Among the major concerns that are preventing the patients from widely adopting this technology are data privacy and security. Wireless Medical Sensor Networks (MSNs) are the building blocks for remote health monitoring systems. This paper helps to identify the most challenging security issues in the existing authentication protocols for remote patient monitoring and presents a lightweight public-key-based authentication protocol for MSNs. In MSNs, the nodes are classified into sensors that report measurements about the human body and actuators that receive commands from the medical staff and perform actions. Authenticating these commands is a critical security issue, as any alteration may lead to serious consequences. The proposed protocol is based on the Rabin authentication algorithm, which is modified in this paper to improve its signature signing process, making it suitable for delay-sensitive MSN applications. To prove the efficiency of the Rabin algorithm, we implemented the algorithm with different hardware settings using Tmote Sky motes and also programmed the algorithm on an FPGA to evaluate its design and performance. Furthermore, the proposed protocol is implemented and tested using the MIRACL (Multiprecision Integer and Rational Arithmetic C/C++) library. The results show that secure, direct, instant and authenticated commands can be delivered from the medical staff to the MSN nodes.

BTG-AC: Break-the-Glass Access Control Model for Medical Data in Wireless Sensor Networks.

Wireless sensor networks (WSNs) have recently attracted much interest in the research community because of their wide range of applications. An emerging application for WSNs involves their use in healthcare where they are generally termed wireless medical sensor networks. In a hospital, outfitting every patient with tiny, wearable, wireless vital sign sensors would allow doctors, nurses, and other caregivers to continuously monitor the state of their patients. In such a scenario, patients are expected to be treated in reasonable time, so an access control model is needed, which will provide both real-time access to comprehensive medical records and detect unauthorized access to sensitive data. In emergency situations, a doctor or nurse needs to access data immediately. The loss in data availability can result in further decline in the patient's condition or can even lead to death. Therefore, the availability of data is more important than any security concern in emergency situations. To address that research issue for medical data in WSNs, we propose the break-the-glass access control (BTG-AC) model that is a modified and redesigned version of the break-the-glass role-based access control (BTG-RBAC) model to address data availability issue and to detect the security policy violations from both authorized and unauthorized users. Several changes within the access control engine are made in BTG-RBAC in order to make the new BTG-AC to apply and fit in WSNs. This paper presents the detailed design and development of the BTG-AC model based on a healthcare scenario. The evaluation results show that the concepts of BTG, prevention and detection mechanism, and obligation provide more flexible access than other current access control models in WSNs. Additionally, we compare the BTG-AC model with an adaptive access control (A2C) model, which has similar properties, for further evaluation. Alongside with the comparison, the advantages and disadvantages of BTG-AC over current WSN access control models are presented.

Efficient anonymous authentication with key agreement protocol for wireless medical sensor networks

The use of wireless medical sensor networks (WMSN) in healthcare has led to a significant progress in this area. WMSN can sense patients’ vital signs and transmit sensed signals to health monitoring devices. Health professionals can monitor the status of patients. Confidentiality and patient privacy are the main concern for the WMSN in health care. Recently, He et al. proposed an authentication protocol for the healthcare applications using WMSN. In this paper, we show that He et al.’s scheme is insecure against various attacks. We also present an improved scheme. In the security analysis, we demonstrate that our scheme is secured against various attacks. We use the BAN logic to prove the correctness of the proposed scheme. As a result, the proposed protocol is practical for healthcare applications.

Wireless medical sensors – context, robustness and safety

Abstract Wireless medical sensors are an emerging technology. Wireless sensors form networks and are placed in an unknown environment. For indoor scenarios context detection of medical sensors, e.g. removal of sensors from a specific room, is important. Current algorithms for context detection of wireless sensors are based on RF signals, but RF signal propagation and room location show only a weak correlation. Recent approaches with RSSI-measurements are based on prior fingerprinting and therefore costly. In our approach, we equip wireless sensor nodes with a barometric sensor to measure pressure disturbances that occur, when doors of rooms are opened or closed. By signal processing of these disturbances our proposed algorithm detects rooms and estimates distances without prior knowledge in an unknown environment. Based on these measurement we automatically build a topology graph representing the room context and distances for indoor environment in a model for buildings. We evaluate our algorithm within a wireless sensor network and show the performance of our solution.

A Study on Reliable Human Healthcare Self-monitoring Capability based Smart Body Situation Correlation Analysis

The convergence of wireless medical sensor networks (WMSNs) and RFID technology have elevated the advancement and sophistication of the self-monitoring capabilities of current u-Healthcare systems. Self-monitoring capability for u-Healthcare systems provides remote and timely real-time feedback of the health status of patients. This paper presents a pervasive architecture of a u-Healthcare system through the optimization of the advanced features of WMSNs and RFID technologies that performs continuous realtime monitoring of patient’s health conditions, thus providing a reliable and efficient healthcare management system.

An improved and anonymous two-factor authentication protocol for health-care applications with wireless medical sensor networks

Wireless sensor networks (WSNs) are fast developed and widely used in many applications. One of the most important applications is wireless medical sensor network (WMSN) which makes modern health-c...

A new authentication protocol for healthcare applications using wireless medical sensor networks with user anonymity

ABSTRACTWith the development and maturation of the wireless communication technologies, the wireless sensor networks have been widely applied in different environments to acquire specific information. The wireless medical sensor networks (WMSNs), as a professional application of the wireless sensor networks in medicine, have attracted more and more attention because of its potential in improving the quality of healthcare services. Through the WMSNs, the parameters of patients' vital signs can be gathered from the sensor nodes equipped on the body of the patients and then can be accessed by the healthcare professionals by using a mobile device. By reason of the open feature of wireless communication, how to guarantee secure communication becomes an important issue. On the other hand, because the vital signs parameters are sensitive to the patients' health status and no one wants to reveal it to the others except the healthcare professionals, the protection of patients' privacy becomes another key issue for WMSNs applications. User authentication protocol with anonymity is the most basic and commonly used method to resolve the security and privacy issues of WMSNs. Recently, He et al. proposed an enhanced authentication protocol for healthcare applications using WMSNs to protect the security and privacy problems. However, we find that their scheme is incorrect in authentication and session key agreement phase. Besides, their scheme has no wrong password detection mechanism, which will not only waste the unnecessary computation and communication costs, but also may deduce the denial of service problem. In this paper, the biometric is introduced as the third authentication factor, and a new user anonymous authentication protocol based on WMSNs is designed so as to remove the drawbacks of the protocol of He et al. Compared with previous protocols, the new presented protocol enhances the security and also keeps the computation efficiency. Copyright © 2015 John Wiley & Sons, Ltd.

Healing on the cloud: Secure cloud architecture for medical wireless sensor networks

There has been a host of research works on wireless sensor networks (WSN) for medical applications. However, the major shortcoming of these efforts is a lack of consideration of data management. Indeed, the huge amount of high sensitive data generated and collected by medical sensor networks introduces several challenges that existing architectures cannot solve. These challenges include scalability, availability and security. Furthermore, WSNs for medical applications provide useful and real information about patients’ health state. This information should be available for healthcare providers to facilitate response and to improve the rescue process of a patient during emergency. Hence, emergency management is another challenge for medical wireless sensor networks. In this paper, we propose an innovative architecture for collecting and accessing large amount of data generated by medical sensor networks. Our architecture overcomes all the aforementioned challenges and makes easy information sharing between healthcare professionals in normal and emergency situations. Furthermore, we propose an effective and flexible security mechanism that guarantees confidentiality, integrity as well as fine-grained access control to outsourced medical data. This mechanism relies on Ciphertext Policy Attribute-based Encryption (CP-ABE) to achieve high flexibility and performance. Finally, we carry out extensive simulations that allow showing that our scheme provides an efficient, fine-grained and scalable access control in normal and emergency situations.

Anomaly Detection in Medical Wireless Sensor Networks using Machine Learning Algorithms

Abstract Wireless sensor networks suffer from a wide range of faults and anomalies which hinder their smooth working. These faults are even more significant for medical wireless sensor networks, which simply cannot afford such inconsistencies. To combat this issue, various fault detection mechanisms have been developed. We tried enhancing the performance of one such mechanism, and our findings are presented in this paper. Using machine learning algorithms, we will show through our experiments on real medical datasets that our approach gives more accurate results than other existing fault detection mechanisms. This research will be critical in detecting sensor faults quickly, accurately and with a low false alarm ratio.