Secure Patient Authentication Framework in the Healthcare System Using Wireless Medical Sensor Networks

Wireless medical sensor networks (WMSNs)-based medical systems are an emerging paradigm of the Internet of Medical Things (IoMT) in which the patients and doctors can access various healthcare services via wireless communication technology without visiting the hospital in person. However, an adversary attempts a variety of security attacks because the sensitive information in various fields is exchanged via an insecure channel. Thus, robust and lightweight authentication protocols are essential for providing dependable healthcare services in WMSN-based medical systems. Recently, Wang et al. (IEEE Internet of Things Journal, doi: 10.1109/JIOT.2021.3117762) proposed blockchain and physically unclonable functions (PUFs)-based lightweight authentication protocol for WMSN. They claimed that their protocol is resistant to cyber and physical security threats and also does provide necessary security requirements. However, we prove that their protocol is vulnerable to various security attacks, such as man-in-the-middle and session key disclosure attacks and also lacks mutual authentication. As a result, we propose a robust authentication protocol for WMSN using blockchain and PUF to address the security problems raised by Wang et al.’s scheme. we assess the security of the proposed scheme by using informal and formal security analyses, such as AVISPA simulation and the ROR oracle model. Furthermore, we present the testbed experiments using Raspberry PI 4 based on MIRACL Crypto SDK. Then, we show the performance of the enhanced scheme compared with related schemes based on testbed experiments. Consequently, our scheme is better suited for practical WMSN-based medical systems because it provides greater security and efficiency than competing schemes.

The advancements in mobile and semiconductor technology resulted in a new area of internet based patient monitoring system called Wireless Medical Sensor Network (WMSN). The transferring of patient sensitive data, aggregated through patient body sensors, over insecure internet, demands for patient identity preserving and data privacy. In this context, many researchers have provided authentication schemes based on various factors. Due to the inherent advantage of light key weight and computation cost, ECC based authentication systems got great demand. Recently Lu et al had provided an authentication and key agreement protocol between WMSN server and user based on ECC. However, in this manuscript, we will demonstrate that Lu et al scheme fails to achieve fundamental requirements of WMSN i.e. preserving user anonymity and resisting impersonation attacks. Further, we propose our robust authentication scheme and we demonstrate the security strengths of our scheme both formally using BAN logic and informally. The formal security analysis confirms that our proposed scheme resists all relevant security attacks.

Wireless medical sensor networks (WMSNs) are used in remote medical service environments to provide patients with convenient healthcare services. In a WMSN environment, patients wear a device that collects their health information and transmits the information via a gateway. Then, doctors make a diagnosis regarding the patient, utilizing the health information. However, this information can be vulnerable to various security attacks because the information is exchanged via an insecure channel. Therefore, a secure authentication scheme is necessary for WMSNs. In 2021, Masud et al. proposed a lightweight and anonymity-preserving user authentication scheme for healthcare environments. We discover that Masud et al.’s scheme is insecure against offline password guessing, user impersonation, and privileged insider attacks. Furthermore, we find that Masud et al.’s scheme cannot ensure user anonymity. To address the security vulnerabilities of Masud et al.’s scheme, we propose a three-factor-based mutual authentication scheme with a physical unclonable function (PUF). The proposed scheme is secure against various security attacks and provides anonymity, perfect forward secrecy, and mutual authentication utilizing biometrics and PUF. To prove the security features of our scheme, we analyze the scheme using informal analysis, Burrows–Abadi–Needham (BAN) logic, the Real-or-Random (RoR) model, and Automated Verification of Internet Security Protocols and Applications (AVISPA) simulation. Furthermore, we estimate our scheme’s security features, computation costs, communication costs, and energy consumption compared with the other related schemes. Consequently, we demonstrate that our scheme is suitable for WMSNs.

The wireless medical sensor networks WMSN play a crucial role in healthcare monitoring remotely. In remote healthcare monitoring, the sensor nodes are deployed in patient's body for collecting physiological data and transmit these data over an insecure channel. The patient's health information is highly sensitive and important. Any malicious modification in physiological data will make wrong diagnoses and harm the patient health. Therefore, privacy, data security, and user authentication are extremely important for accessing patient's real-time heath information over an insecure channel. In this regard, this article proposes a secure and robust two-factor based remote user authentication protocol for healthcare monitoring. The authentication proof has done with the help of BAN logic, which ensures that the proposed scheme provides mutual authentication and session key agreement securely. The informal security verification proves that the developed protocol is secure from various security attacks. The simulation of the proposed scheme has been done using AVISPA tool, whose simulation results confirm that the proposed scheme is secure from active and passive attacks. Performance evaluation shows that the proposed protocol is efficient in terms of security features, computation cost, communication cost, and execution time.

With the rapid growth of wireless medical sensor networks (WMSNs) based healthcare applications, protecting both the privacy and security from illegitimate users, are major concern issues since patient’s precise information is vital for the proper diagnosis procedure. So, authentication protocol is one of the efficient mechanisms to deal with trustworthy and authentic users. Several authentication protocols have been proposed in WMSNs environment. However, the most of these protocols are so susceptible to security threats and not suitable for practical use. In this article, recently proposed Amin et al.’s authentication scheme is reviewed and some vulnerabilities like off-line password guessing attack, user impersonation attack, known session-key temporary information attack, the revelation of secret parameters, and identity guessing attack are pointed out. To overcome all the above mentioned vulnerabilities, we have proposed an enhanced three-factor based remote user authentication protocol in WMSNs environment. Further, the proposed protocol is validated using Burrows–Abadi–Needham logic and then simulated using Automated Validation of Internet Security Protocols and Applications tool. Moreover, the security analysis ensures that the proposed protocol is well protected from various types of malicious attacks. In addition, the performance evaluation shows better efficiency and suitability of our protocol over other related protocols.

Since the Internet of Things (IoT) will be entwined with everything we use in our daily life, the consequence of security flaws escalates. Smart objects will govern most of the home appliances and car engines yielding potential disaster scenarios. In this context, successful attacks could lead to chaos and scary scenarios (www.darkreading.com). Unprotected personal information may expose sensitive and embarrassing data to the public and attacks may threaten not only our computers and smart devices, but our intimacy and perhaps our lives too. Because persons and objects will be bonded with each other, user consent becomes critical. Therefore, thing, object, and user Identity will be the focus of future IoT security solutions, yielding a Trust, Security, and Privacy (TSP) paradigm, which may constitute the Achilles' heel of IoT. While security issues are quite straightforward, mainly from background knowledge, privacy issues are far more complex. Privacy constitutes a rather challenging task, even for the m...

The Internet of Things (IoT) enables all objects to connect to the Internet and exchange data via different emerging technologies, which makes the intelligent identification and management a reality. Wireless sensor networks (WSNs), as a crucial basis of IoT, have been applied in many fields like smart health care and smart transportation. With the development of WSNs, data security has attracted more and more attention, and user authentication is a popular mechanism to ensure the information security of WSNs. Recently, many authentication mechanisms for wireless medical sensor networks (WMSNs) have been proposed, but most of the protocols cannot achieve the features of local password change and forward secrecy while resisting stolen smart card attack. To enhance the security based on previous work, an ECC-based secure three-factor authentication protocol with forward secrecy for WMSN is proposed in this paper. It utilizes a fuzzy commitment scheme to handle the biometric information. Meanwhile, fuzzy verifier and honey_list techniques are used to solve the contradiction of local password verification and mobile device lost attack. The security of our protocol is evaluated by provable security, Proverif tool, and information analysis. Besides, the comparisons with the relevant protocols are given, and the results indicate that our protocol is robust and secure for WMSN systems.

Recent growth in the Internet of Things (IoT) looks promising for realizing a smart environment of the future. However, concerns about the security of IoT devices are escalating as they are inherently constrained by limited resources, heterogeneity, and lack of standard security controls or protocols. Due to their inability to support state-of-the-art secure network protocols and defense mechanisms, standard security solutions are unsuitable for dynamic IoT environments that require large and smart IoT infrastructure deployments. At present, the IoT based smart environment deployments predominantly use cloud-centric approaches to enable continuous and on-demand data exchange that leads to further security and privacy risks. While standard security protocols, such as Virtual Private Networks (VPNs), have been explored for certain IoT environments recently, the implementation models reported have several variations and are not practically scalable for any dynamically scalable IoT deployment. This paper addresses current drawbacks in providing the required flexibility, interoperability, scalability, and low-cost practical viability of a secure IoT infrastructure. We propose an adaptive end-to-end security model that supports the defense requirements for a scalable IoT infrastructure. With low-cost embedded controllers, such as the Raspberry Pi, allowing for the convergence of more sophisticated networking protocols to be embedded at the IoT monitoring interface, we propose a scalable IoT security model integrating both the IoT devices and the controller as one embedded device. Our approach is unique, with a focus on the integration of a security protocol at the embedded interface. In addition, we demonstrate a prototype implementation of our IoT security model for a smart water monitoring system. We believe that our modest first step would instill future research interests in this direction.

Smart, linked healthcare systems are made possible by the fast developments in the Internet of Things (IoT), which have greatly changed healthcare. Wearable sensors combined with IoT technology let continuous real-time tracking of important physiological indicators including heart rate, blood pressure, oxygen saturation, glucose levels, and body temperature. By means of early disease identification, remote monitoring, and prompt medical interventions, these systems improve patient care and lower hospital visits, hence increasing healthcare efficiency. By sending real-time health data to cloud-based systems, IoT-driven healthcare solutions improve data-driven decision-making and let healthcare personnel evaluate patient status from a distance. Widespread adoption will depend on issues including data privacy, cyber security threats, interoperability, and energy efficiency even with all the advantages. This article investigates how IoT and wearable sensors fit into contemporary healthcare, hence affecting real-time patient monitoring, healthcare access, and general patient outcomes.

Recent research efforts have created rapid advances in the field of the Internet of Things (IoT) in terms of communication protocols, sensing technologies, computing capabilities, next-generation wireless technologies, big data and AI techniques, and on-device, edge, cloud processing. These advances created a paradigm shift and generated a wide range of potential opportunities for a new major field known as the Internet of Medical Things (IoMT), as well as subfields like mobile Health (mHeatlh) and digital or electronic Health (eHealth). This paper provides an overview of the Internet of Medical Things and presents a classification to define the primary users and their roles and involvement in smart healthcare systems. The paper then presents taxonomy on the deployment scales of different healthcare environments, from personal healthcare to widescale connected healthcare systems. The overview also discusses the n-tier architecture of IoMT, then presents a set of taxonomies and classifications on the different medical devices used in healthcare systems as well as non-medical devices used to provide context-aware information about the surrounding environment. The paper then concludes the overview by presenting the different healthcare-related applications and services, a comparison between traditional and smart healthcare systems, and the different obstacles and challenges in the field of IoMT to guide the development of new services and devices. Many survey papers in the literature focused on similar points; however, up to our knowledge, this is the first paper to present taxonomies and classifications for these IoMT essential topics. The presented taxonomies and classifications provide the manufacturers of medical devices and the developers of healthcare services a deeper understanding of the healthcare systems’ landscape to address different requirements and demands.

The Internet of Things (IoT) is an innovative technology with billions of sensors in various IoT applications. Important elements used in the IoT are sensors that collect data for desired analyses. The IoT and sensors are very important in smart cities, smart agriculture, smart education, healthcare systems, and other applications. The healthcare system uses the IoT to meet global health challenges, and the newest example is COVID-19. Demand has increased during COVID-19 for healthcare to reach patients remotely and digitally at their homes. The IoT properly monitors patients using an interconnected network to overcome the issues of healthcare services. The aim of this paper is to discuss different applications, technologies, and challenges related to the healthcare system. Different databases were searched using keywords in Google Scholar, Elsevier, PubMed, ACM, ResearchGate, Scopus, Springer, etc. This paper discusses, highlights, and identifies the applications of IoT healthcare systems to provide research directions to healthcare, academia, and researchers to overcome healthcare system challenges. Hence, the IoT can be beneficial by providing better treatments using the healthcare system efficiently. In this paper, the integration of the IoT with smart technologies not only improves computation, but will also allow the IoT to be pervasive, profitable, and available anytime and anywhere. Finally, some future directions and challenges are discussed, along with useful suggestions that can assist the IoT healthcare system during COVID-19 and in a severe pandemic.

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.

The Internet of Things (IoT) is a constantly growing environment for connecting hardware, software, physical things, and communicating devices altogether or individually over a network with or without human interventions. It collects, computes, and exchanges data together. This quality of IoT makes the platform flexible for the variety of applications that work on this technology to get incredible benefits, including healthcare domains. In the olden days, the medical system does not have any digital file system, clinical data monitoring, and cyber-physical systems. Cyber Physical System (CPS) is the nucleus of IoT. The smart parameters of IoT create an interesting thing on the Internet of Healthcare System (IoHT) and keep the best place in revenue. Apart from smart homes, cities, and smart devices, IoT established a vital position in IoT. The security and the privacy of Healthcare data should be managed properly. Thus, making a new concept into it called, “Blockchain.” This not only marks its step in cryptocurrencies, but it also tights the security and privacy of all types of data, and it supports heterogeneous applications, especially IoT-based applications. This article describes the Blockchain-IoT-based healthcare applications, security of the Internet of Medical Things (IoMT), and the future direction in the healthcare system based on Blockchain.

The Internet of Medical Things (IoMT) is an online device that senses and transmits medical data from users to physicians within a time interval. In, recent years, IoMT has rapidly grown in the medical field to provide healthcare services without physical appearance. With the use of sensors, IoMT applications are used in healthcare management. In such applications, one of the most important factors is data security, given that its transmission over the network may cause obtrusion. For data security in IoMT systems, blockchain is used due to its numerous blocks for secure data storage. In this study, Blockchain-assisted secure data management framework (BSDMF) and Proof of Activity (PoA) protocol using malicious code detection algorithm is used in the proposed data security for the healthcare system. The main aim is to enhance the data security over the networks. The PoA protocol enhances high security of data from the literature review. By replacing the malicious node from the block, the PoA can provide high security for medical data in the blockchain. Comparison with existing systems shows that the proposed simulation with BSD-Malicious code detection algorithm achieves higher accuracy ratio, precision ratio, security, and efficiency and less response time for Blockchain-enabled healthcare systems.

A wireless sensor network is used to sense the infected person's body condition and transmits the collected data to the database. The details including temperature, heartbeat, and blood pressure are sensed using appropriate sensors and stored in the servers. The details are encrypted using Paillier and ElGamal key cryptosystems for providing high security. The server is helpful in providing querying service to users. The encrypted data is fetched from the server and decrypted before authentication. To prevent the patient data from the attackers, new protocol is proposed, where the patient details are converted into numerical form. This numerical form is difficult to understand by the attackers. Then the numerical values are sent to servers through secure channels. The patient data are securely distributed by employing the Paillier and ElGamal cryptosystems. This project focuses on secure storage and communication. The secure data will be implemented based on cryptographic principle.